In [1]:
import numpy as np
import pandas as pd
import tensorflow as tf
import matplotlib.pyplot as plt
%matplotlib inline
import re
from sklearn.preprocessing import scale
from nltk.corpus import stopwords
import nltk

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import collections
import math
import os
import random
import zipfile

import numpy as np
from six.moves import urllib
from six.moves import xrange  # pylint: disable=redefined-builtin
import tensorflow as tf

In [2]:
df = pd.read_csv('./data/announcements.csv')
print(df)


                                                  Title  \
0            Need a Ride from Indy Airport back to Rose   
1     Yet another person asking for a ride back from...   
2                           Another ride back to campus   
3                                   Ride back to Campus   
4                      Requesting a ride back to campus   
5                               Bring back your change!   
6                                        Ride from Indy   
7                         Need a Ride Form Indi Airport   
8                     Need a ride from Indy *on Monday*   
9                   Need Ride from Indy Airport to Rose   
10    Looking for a ride from Indianapolis airport t...   
11                                  Ride back from Indy   
12                                  Ride back to Campus   
13                                        Ride from IND   
14                       Ride from Indy Airport to Rose   
15                Need a ride from Indy Airport to Rose   
16                                    Selling Ti-Nspire   
17           Selling Logitech Wireless Wave Combo Mk550   
18        Seminar: Hosted by Chemistry and Biochemistry   
19                             Car Audio parts For Sale   
20                        NOOK Color 7" tablet for sale   
21                                      Need Xbox 360's   
22                              Looking for ME 323 Book   
23                                       SAVE THE DATE!   
24    NEW - TV, PS3, Apple TV, Dyson, Rosetta Stone,...   
25             January Institute Meeting Minutes Posted   
26                                            Lost Keys   
27                                    Found Galaxy SIII   
28                                             3D Event   
29    SimplyWell Speaker - Stress Management - Wedne...   
...                                                 ...   
4137                              Lost TI-89 Calculator   
4138                            Housemate for 2015-2016   
4139      Spring Swim Lesson Registration opens today!!   
4140                   Room for rent $150/mo March-June   
4141    Selling iPod touch 64 GB and Nexus 7(2013) 32GB   
4142      Survey for Class Project - Please Participate   
4143                                          Sub lease   
4144                                       Found Huskie   
4145   Alpha Phi Omega Info Session and Free Ice Cream!   
4146  Xbox 360 Slim, Two Controllers,7 Games $120 - ...   
4147                                          Found Dog   
4148                                Found: Fitbit Piece   
4149                       Forget your phone somewhere?   
4150                                    Airport Shuttle   
4151                                        Giving ride   
4152               Looking for a ride to Chicago O'Hare   
4153                                       Found iPhone   
4154                               Subletting Apartment   
4155  WHITE AUDI A4 (or other sedan) LIGHTS ON PERCO...   
4156  WHITE AUDI A4 (or other sedan) LIGHTS ON PERCO...   
4157                                Selling AOC monitor   
4158             Class Project - Survey about Evolution   
4159                                 Lost Letter Jacket   
4160                                 Lost Letter Jacket   
4161                                          LOST: Hat   
4162                                         Need Boxes   
4163                               Looking for used PS3   
4164                                         Thank You!   
4165                                    Missing Glasses   
4166                        Need Ride to Rose From Indy   

                                                   Body  
0     Happy New Year everyone! I am looking for a ri...  
1     My flight lands at 3:45pm on Saturday\nI am wi...  
2     I am looking for a ride back to campus from th...  
3     I was hoping someone may be able to give me a ...  
4     My flight lands at 3:45pm. I am willing to pay...  
5     Don't forget to bring your change back to camp...  
6     Hi, sorry for yet another email about this, bu...  
7     Hey, my name is Eshan Nayyar and I need a ride...  
8     Hey all,\n\nMy flight lands in Indy about 1:15...  
9     My flight lands on Sunday at 8:24PM, I will be...  
10    I arrive in Indianapolis Airport at Saturday A...  
11    My flight lands at 11:30 pm on sunday. Is ther...  
12    .ExternalClassA87E48F2968B497F900856F9046EE024...  
13    Flight arrives at 6AM. I'm wondering if anyone...  
14    I am at the airport right now, and I need a ri...  
15    My flight lands at 6:50 PM today and I really ...  
16    Original Ti-Nspire, no CAS, has both Nspire an...  
17    Item is like new, with all factory plastic wra...  
18    January 9, 2013\nGM315\n \nThe Sagle Group At ...  
19    I am selling 2 RE audio SX 18" subwoofers\nThe...  
20    I have a 7" Nook Color tablet I bought for a C...  
21    If you have an Xbox 360, working or not, that ...  
22    I am looking for a ME 323 book (Comp Apps 2). ...  
23    SAVE THE DATE!!!\n \n\n\n\n\n\n\n\n\n\n\n\n\nI...  
24    Please see the attached document for informati...  
25    The meeting minutes for the January 8, 2013 In...  
26    I seem to have misplaced my car keys, they are...  
27    If you happened to misplace your Galaxy S3 upo...  
28    The Mathematics Department's new 3D workstatio...  
29    Stress Management\nWednesday, January 30, 2013...  
...                                                 ...  
4137  ​ I lost my TI-89 calculator, and I don't reme...  
4138  Hello!I am looking for a housemate for next ye...  
4139  Registration is now open for our annual spring...  
4140  Looking for a roommate or two for the ​spring ...  
4141  Selling blue iPod Touch 5th gen 64GB for $150 ...  
4142  Students, please fill out this short survey fo...  
4143  ​I have  one room sublease avaible for this sp...  
4144  ​I found a huskie wandering around at ashton i...  
4145  Alpha Phi Omega is a co-ed service fraturnity ...  
4146  ​Selling this console, still in great conditio...  
4147  ​Last night we found a dog roaming around in o...  
4148  A reddish colored Fitbit piece was found and t...  
4149  ​found someones samsung Galaxy with a Blue cas...  
4150  Hi all!I need a ride to the Indianapolis Airpo...  
4151  Hey, I'm heading to Indy tomorrow morning at a...  
4152  ​Hey,​I'm looking for a ride to chicago O'Hare...  
4153  ​An iPhone was found in the men's restroom on ...  
4154  ​I am looking to sublet my apartment to someon...  
4155  32D0E824606B40F184C43B0ACB47AB9A p.MsoNormal, ...  
4156  268915D1018F4F64AF0EB89542631E9E p.MsoNormal, ...  
4157  ​I got an AOC e1649fwu monitor, It's like new ...  
4158  ​Students, please complete this short survey r...  
4159  Hello,Sorry for the spam. I seem to have lost ...  
4160  Hello,Sorry for the spam. I seem to have lost ...  
4161  It's a Gray Fedora. ​Lost somewhere between th...  
4162  I am in need of some boxes, medium and large s...  
4163  ​Hi,​I am interested in buying an used PS3.  O...  
4164  ​For the person who found my red notebook and ...  
4165  ​I am missing a pair of black mens Seiko presc...  
4166  Will be arriving in Indy airport tonight by 11...  

[4167 rows x 2 columns]

In [10]:
titles = df.icol(0)
body = df.icol(1)
body.shape


/opt/anaconda3/lib/python3.5/site-packages/ipykernel/__main__.py:1: FutureWarning: icol(i) is deprecated. Please use .iloc[:,i]
  if __name__ == '__main__':
/opt/anaconda3/lib/python3.5/site-packages/ipykernel/__main__.py:2: FutureWarning: icol(i) is deprecated. Please use .iloc[:,i]
  from ipykernel import kernelapp as app
Out[10]:
(4167,)

In [11]:
body = body.reshape(4167,1)
titles = titles.reshape(4167,1)

In [12]:
N = 4167

In [14]:
def sentence_to_words( sentence ):
    # Function to convert a raw review to a string of words
    # The input is a single string (a raw movie review), and 
    # the output is a single string (a preprocessed movie review)
    #
    # 2. Remove non-letters        
    letters_only = re.sub("[^a-zA-Z]", " ", sentence) 
    #
    # 3. Convert to lower case, split into individual words
    words = letters_only.lower().split()                             
    #
    # 4. In Python, searching a set is much faster than searching
    #   a list, so convert the stop words to a set
    stops = set(stopwords.words("english"))                  
    # 
    # 5. Remove stop words
    meaningful_words = [w for w in words if not w in stops]   
    #
    # 6. Join the words back into one string separated by space, 
    # and return the result.
    #return( " ".join( meaningful_words ))  
    return meaningful_words

In [6]:
def sentence_to_words( sentence ):
    # Function to convert a raw review to a string of words
    # The input is a single string (a raw movie review), and 
    # the output is a single string (a preprocessed movie review)
    #
    # 2. Remove non-letters        
    letters_only = re.sub("[^a-zA-Z]", " ", sentence) 
    #
    # 3. Convert to lower case, split into individual words
    words = letters_only.lower().split()                             
    #
    # 4. In Python, searching a set is much faster than searching
    #   a list, so convert the stop words to a set
    stops = set(stopwords.words("english"))                  
    # 
    # 5. Remove stop words
    meaningful_words = [w for w in words if not w in stops]   
    #
    # 6. Join the words back into one string separated by space, 
    # and return the result.
    #return( " ".join( meaningful_words ))  
    return meaningful_words

In [15]:
sentence_to_words(titles[0][0])


Out[15]:
['need', 'ride', 'indy', 'airport', 'back', 'rose']

In [16]:
def email_to_words():
    list = []
    for i in range(N):
        array = sentence_to_words(titles[i][0])
        list.extend(array)
        if(isinstance(body[i][0], str)):
            array = sentence_to_words(body[i][0])
            list.extend(array)
    return list

In [17]:
list = email_to_words()
len(list)


Out[17]:
159378

In [18]:
words = list
count = [['UNK', -1]]

In [19]:
# Step 2: Build the dictionary and replace rare words with UNK token.
vocabulary_size = 3000

In [20]:
def build_dataset(words):
    count = [['UNK', -1]]
    count.extend(collections.Counter(words).most_common(vocabulary_size - 1))
    dictionary = dict()
    for word, _ in count:
        dictionary[word] = len(dictionary)
    data = []
    unk_count = 0
    for word in words:
        if word in dictionary:
            index = dictionary[word]
        else:
            index = 0  # dictionary['UNK']
            unk_count += 1
        data.append(index)
    count[0][1] = unk_count
    reverse_dictionary = dict(zip(dictionary.values(), dictionary.keys()))
    return data, count, dictionary, reverse_dictionary

In [21]:
data, count, dictionary, reverse_dictionary = build_dataset(words)

In [22]:
del words  # Hint to reduce memory.

In [23]:
print('Most common words (+UNK)', count[:5])


Most common words (+UNK) [['UNK', 20378], ('rose', 3020), ('hulman', 2705), ('edu', 2386), ('please', 1651)]

In [24]:
print('Sample data', data[:10], [reverse_dictionary[i] for i in data[:10]])


Sample data [17, 11, 34, 39, 42, 1, 601, 27, 63, 161] ['need', 'ride', 'indy', 'airport', 'back', 'rose', 'happy', 'new', 'year', 'everyone']

In [25]:
data_index = 0

In [26]:
# Step 3: Function to generate a training batch for the skip-gram model.
def generate_batch(batch_size, num_skips, skip_window):
    global data_index
    assert batch_size % num_skips == 0
    assert num_skips <= 2 * skip_window
    batch = np.ndarray(shape=(batch_size), dtype=np.int32)
    labels = np.ndarray(shape=(batch_size, 1), dtype=np.int32)
    span = 2 * skip_window + 1 # [ skip_window target skip_window ]
    buffer = collections.deque(maxlen=span)
    for _ in range(span):
        buffer.append(data[data_index])
        data_index = (data_index + 1) % len(data)
    for i in range(batch_size // num_skips):
        target = skip_window  # target label at the center of the buffer
        targets_to_avoid = [ skip_window ]
        for j in range(num_skips):
            while target in targets_to_avoid:
                target = random.randint(0, span - 1)
            targets_to_avoid.append(target)
            batch[i * num_skips + j] = buffer[skip_window]
            labels[i * num_skips + j, 0] = buffer[target]
        buffer.append(data[data_index])
        data_index = (data_index + 1) % len(data)
    return batch, labels

In [27]:
batch, labels = generate_batch(batch_size=8, num_skips=2, skip_window=1)

In [28]:
for i in range(8):
    print(batch[i], reverse_dictionary[batch[i]],
      '->', labels[i, 0], reverse_dictionary[labels[i, 0]])


11 ride -> 17 need
11 ride -> 34 indy
34 indy -> 11 ride
34 indy -> 39 airport
39 airport -> 34 indy
39 airport -> 42 back
42 back -> 1 rose
42 back -> 39 airport

In [29]:
# Step 4: Build and train a skip-gram model.
batch_size = 128
embedding_size = 128  # Dimension of the embedding vector.
skip_window = 1       # How many words to consider left and right.
num_skips = 2         # How many times to reuse an input to generate a label.

In [30]:
# We pick a random validation set to sample nearest neighbors. Here we limit the
# validation samples to the words that have a low numeric ID, which by
# construction are also the most frequent.
valid_size = 16     # Random set of words to evaluate similarity on.
valid_window = 100  # Only pick dev samples in the head of the distribution.
valid_examples = np.random.choice(valid_window, valid_size, replace=False)
num_sampled = 64    # Number of negative examples to sample.

In [31]:
graph = tf.Graph()

In [32]:
with graph.as_default():

    # Input data.
    train_inputs = tf.placeholder(tf.int32, shape=[batch_size])
    train_labels = tf.placeholder(tf.int32, shape=[batch_size, 1])
    valid_dataset = tf.constant(valid_examples, dtype=tf.int32)
    # Ops and variables pinned to the CPU because of missing GPU implementation
    with tf.device('/cpu:0'):
    # Look up embeddings for inputs.
        embeddings = tf.Variable(tf.random_uniform([vocabulary_size, embedding_size], -1.0, 1.0))
        embed = tf.nn.embedding_lookup(embeddings, train_inputs)

        # Construct the variables for the NCE loss
        nce_weights = tf.Variable(
               tf.truncated_normal([vocabulary_size, embedding_size],
                        stddev=1.0 / math.sqrt(embedding_size)))
    nce_biases = tf.Variable(tf.zeros([vocabulary_size]))
    # Compute the average NCE loss for the batch.
    # tf.nce_loss automatically draws a new sample of the negative labels each
    # time we evaluate the loss.
    loss = tf.reduce_mean(tf.nn.nce_loss(nce_weights, nce_biases, embed, train_labels,
                     num_sampled, vocabulary_size))
    # Construct the SGD optimizer using a learning rate of 1.0.
    optimizer = tf.train.GradientDescentOptimizer(1.0).minimize(loss)
     # Compute the cosine similarity between minibatch examples and all embeddings.
    norm = tf.sqrt(tf.reduce_sum(tf.square(embeddings), 1, keep_dims=True))
    normalized_embeddings = embeddings / norm
    valid_embeddings = tf.nn.embedding_lookup(normalized_embeddings, valid_dataset)
    similarity = tf.matmul(valid_embeddings, normalized_embeddings, transpose_b=True)

    # Add variable initializer.
    init = tf.initialize_all_variables()
    saver = tf.train.Saver()  # Gets all variables in `graph`.

In [33]:
# Step 5: Begin training.
num_steps = 100001
#num_steps = 10

In [34]:
with tf.Session(graph=graph) as session:
    # We must initialize all variables before we use them.
    init.run()
    print("Initialized")

    average_loss = 0
    for step in xrange(num_steps):
        batch_inputs, batch_labels = generate_batch(
            batch_size, num_skips, skip_window)
        feed_dict = {train_inputs : batch_inputs, train_labels : batch_labels}

        # We perform one update step by evaluating the optimizer op (including it
        # in the list of returned values for session.run()
        _, loss_val = session.run([optimizer, loss], feed_dict=feed_dict)
        average_loss += loss_val
        if step % 2000 == 0:
            if step > 0:
                average_loss /= 2000
            # The average loss is an estimate of the loss over the last 2000 batches.
            print("Average loss at step ", step, ": ", average_loss)
            average_loss = 0


     
         # Note that this is expensive (~20% slowdown if computed every 500 steps)
        if step % 10000 == 0:
            sim = similarity.eval()
            for i in xrange(valid_size):
                valid_word = reverse_dictionary[valid_examples[i]]
                top_k = 8 # number of nearest neighbors
                nearest = (-sim[i, :]).argsort()[1:top_k+1]
                log_str = "Nearest to %s:" % valid_word
                for k in xrange(top_k):
                    close_word = reverse_dictionary[nearest[k]]
                    log_str = "%s %s," % (log_str, close_word)
                    print(log_str)
    final_embeddings = normalized_embeddings.eval()
    save_path = saver.save(session, "./data/model.ckpt")


Initialized
Average loss at step  0 :  199.10067749
Nearest to family: theta,
Nearest to family: theta, business,
Nearest to family: theta, business, latest,
Nearest to family: theta, business, latest, station,
Nearest to family: theta, business, latest, station, item,
Nearest to family: theta, business, latest, station, item, properties,
Nearest to family: theta, business, latest, station, item, properties, questions,
Nearest to family: theta, business, latest, station, item, properties, questions, close,
Nearest to engineering: mark,
Nearest to engineering: mark, functions,
Nearest to engineering: mark, functions, seem,
Nearest to engineering: mark, functions, seem, much,
Nearest to engineering: mark, functions, seem, much, academics,
Nearest to engineering: mark, functions, seem, much, academics, ghz,
Nearest to engineering: mark, functions, seem, much, academics, ghz, management,
Nearest to engineering: mark, functions, seem, much, academics, ghz, management, height,
Nearest to serif: button,
Nearest to serif: button, graduate,
Nearest to serif: button, graduate, field,
Nearest to serif: button, graduate, field, offered,
Nearest to serif: button, graduate, field, offered, remote,
Nearest to serif: button, graduate, field, offered, remote, human,
Nearest to serif: button, graduate, field, offered, remote, human, brainard,
Nearest to serif: button, graduate, field, offered, remote, human, brainard, ports,
Nearest to help: vga,
Nearest to help: vga, developers,
Nearest to help: vga, developers, sunglasses,
Nearest to help: vga, developers, sunglasses, maker,
Nearest to help: vga, developers, sunglasses, maker, environment,
Nearest to help: vga, developers, sunglasses, maker, environment, volunteer,
Nearest to help: vga, developers, sunglasses, maker, environment, volunteer, western,
Nearest to help: vga, developers, sunglasses, maker, environment, volunteer, western, questions,
Nearest to cell: vacuum,
Nearest to cell: vacuum, banner,
Nearest to cell: vacuum, banner, src,
Nearest to cell: vacuum, banner, src, like,
Nearest to cell: vacuum, banner, src, like, imgur,
Nearest to cell: vacuum, banner, src, like, imgur, clicking,
Nearest to cell: vacuum, banner, src, like, imgur, clicking, paper,
Nearest to cell: vacuum, banner, src, like, imgur, clicking, paper, presenter,
Nearest to know: hold,
Nearest to know: hold, flat,
Nearest to know: hold, flat, safe,
Nearest to know: hold, flat, safe, presentation,
Nearest to know: hold, flat, safe, presentation, heat,
Nearest to know: hold, flat, safe, presentation, heat, hare,
Nearest to know: hold, flat, safe, presentation, heat, hare, jack,
Nearest to know: hold, flat, safe, presentation, heat, hare, jack, obo,
Nearest to found: study,
Nearest to found: study, determine,
Nearest to found: study, determine, edu,
Nearest to found: study, determine, edu, ray,
Nearest to found: study, determine, edu, ray, tear,
Nearest to found: study, determine, edu, ray, tear, bc,
Nearest to found: study, determine, edu, ray, tear, bc, bracelet,
Nearest to found: study, determine, edu, ray, tear, bc, bracelet, lake,
Nearest to used: cee,
Nearest to used: cee, cross,
Nearest to used: cee, cross, download,
Nearest to used: cee, cross, download, finish,
Nearest to used: cee, cross, download, finish, pool,
Nearest to used: cee, cross, download, finish, pool, disc,
Nearest to used: cee, cross, download, finish, pool, disc, display,
Nearest to used: cee, cross, download, finish, pool, disc, display, insignia,
Nearest to airport: soccer,
Nearest to airport: soccer, block,
Nearest to airport: soccer, block, cbe,
Nearest to airport: soccer, block, cbe, wiki,
Nearest to airport: soccer, block, cbe, wiki, record,
Nearest to airport: soccer, block, cbe, wiki, record, adc,
Nearest to airport: soccer, block, cbe, wiki, record, adc, switch,
Nearest to airport: soccer, block, cbe, wiki, record, adc, switch, listing,
Nearest to pm: generic,
Nearest to pm: generic, startup,
Nearest to pm: generic, startup, cdb,
Nearest to pm: generic, startup, cdb, towards,
Nearest to pm: generic, startup, cdb, towards, biomedical,
Nearest to pm: generic, startup, cdb, towards, biomedical, privacy,
Nearest to pm: generic, startup, cdb, towards, biomedical, privacy, village,
Nearest to pm: generic, startup, cdb, towards, biomedical, privacy, village, appears,
Nearest to underline: anything,
Nearest to underline: anything, often,
Nearest to underline: anything, often, dont,
Nearest to underline: anything, often, dont, membership,
Nearest to underline: anything, often, dont, membership, bad,
Nearest to underline: anything, often, dont, membership, bad, ab,
Nearest to underline: anything, often, dont, membership, bad, ab, built,
Nearest to underline: anything, often, dont, membership, bad, ab, built, yesterday,
Nearest to percopo: prepare,
Nearest to percopo: prepare, pockets,
Nearest to percopo: prepare, pockets, processes,
Nearest to percopo: prepare, pockets, processes, black,
Nearest to percopo: prepare, pockets, processes, black, negotiable,
Nearest to percopo: prepare, pockets, processes, black, negotiable, use,
Nearest to percopo: prepare, pockets, processes, black, negotiable, use, basics,
Nearest to percopo: prepare, pockets, processes, black, negotiable, use, basics, retirement,
Nearest to div: hosting,
Nearest to div: hosting, couponing,
Nearest to div: hosting, couponing, speed,
Nearest to div: hosting, couponing, speed, ends,
Nearest to div: hosting, couponing, speed, ends, text,
Nearest to div: hosting, couponing, speed, ends, text, jan,
Nearest to div: hosting, couponing, speed, ends, text, jan, offices,
Nearest to div: hosting, couponing, speed, ends, text, jan, offices, message,
Nearest to externalclass: offices,
Nearest to externalclass: offices, anytime,
Nearest to externalclass: offices, anytime, screen,
Nearest to externalclass: offices, anytime, screen, flight,
Nearest to externalclass: offices, anytime, screen, flight, ride,
Nearest to externalclass: offices, anytime, screen, flight, ride, diabetes,
Nearest to externalclass: offices, anytime, screen, flight, ride, diabetes, ebc,
Nearest to externalclass: offices, anytime, screen, flight, ride, diabetes, ebc, perfect,
Nearest to free: resolution,
Nearest to free: resolution, cbe,
Nearest to free: resolution, cbe, windows,
Nearest to free: resolution, cbe, windows, bundle,
Nearest to free: resolution, cbe, windows, bundle, county,
Nearest to free: resolution, cbe, windows, bundle, county, week,
Nearest to free: resolution, cbe, windows, bundle, county, week, listing,
Nearest to free: resolution, cbe, windows, bundle, county, week, listing, making,
Nearest to margin: biology,
Nearest to margin: biology, saddle,
Nearest to margin: biology, saddle, dorm,
Nearest to margin: biology, saddle, dorm, thesis,
Nearest to margin: biology, saddle, dorm, thesis, shoe,
Nearest to margin: biology, saddle, dorm, thesis, shoe, afternoon,
Nearest to margin: biology, saddle, dorm, thesis, shoe, afternoon, leg,
Nearest to margin: biology, saddle, dorm, thesis, shoe, afternoon, leg, easily,
Average loss at step  2000 :  15.0230640922
Average loss at step  4000 :  4.24291721773
Average loss at step  6000 :  3.91071711886
Average loss at step  8000 :  3.74769697905
Average loss at step  10000 :  3.66144348145
Nearest to family: theta,
Nearest to family: theta, sans,
Nearest to family: theta, sans, business,
Nearest to family: theta, sans, business, latest,
Nearest to family: theta, sans, business, latest, station,
Nearest to family: theta, sans, business, latest, station, interaction,
Nearest to family: theta, sans, business, latest, station, interaction, c,
Nearest to family: theta, sans, business, latest, station, interaction, c, externalclassc,
Nearest to engineering: mark,
Nearest to engineering: mark, functions,
Nearest to engineering: mark, functions, ead,
Nearest to engineering: mark, functions, ead, flag,
Nearest to engineering: mark, functions, ead, flag, management,
Nearest to engineering: mark, functions, ead, flag, management, seem,
Nearest to engineering: mark, functions, ead, flag, management, seem, statistics,
Nearest to engineering: mark, functions, ead, flag, management, seem, statistics, eec,
Nearest to serif: field,
Nearest to serif: field, dbded,
Nearest to serif: field, dbded, button,
Nearest to serif: field, dbded, button, graduate,
Nearest to serif: field, dbded, button, graduate, sharp,
Nearest to serif: field, dbded, button, graduate, sharp, onto,
Nearest to serif: field, dbded, button, graduate, sharp, onto, f,
Nearest to serif: field, dbded, button, graduate, sharp, onto, f, remote,
Nearest to help: vga,
Nearest to help: vga, developers,
Nearest to help: vga, developers, sounds,
Nearest to help: vga, developers, sounds, questions,
Nearest to help: vga, developers, sounds, questions, sunglasses,
Nearest to help: vga, developers, sounds, questions, sunglasses, maker,
Nearest to help: vga, developers, sounds, questions, sunglasses, maker, appreciate,
Nearest to help: vga, developers, sounds, questions, sunglasses, maker, appreciate, rotation,
Nearest to cell: vacuum,
Nearest to cell: vacuum, imgur,
Nearest to cell: vacuum, imgur, clicking,
Nearest to cell: vacuum, imgur, clicking, src,
Nearest to cell: vacuum, imgur, clicking, src, processes,
Nearest to cell: vacuum, imgur, clicking, src, processes, banner,
Nearest to cell: vacuum, imgur, clicking, src, processes, banner, eec,
Nearest to cell: vacuum, imgur, clicking, src, processes, banner, eec, andrew,
Nearest to know: hold,
Nearest to know: hold, flat,
Nearest to know: hold, flat, externalclassbd,
Nearest to know: hold, flat, externalclassbd, anna,
Nearest to know: hold, flat, externalclassbd, anna, hare,
Nearest to know: hold, flat, externalclassbd, anna, hare, safe,
Nearest to know: hold, flat, externalclassbd, anna, hare, safe, fafsa,
Nearest to know: hold, flat, externalclassbd, anna, hare, safe, fafsa, letter,
Nearest to found: lost,
Nearest to found: lost, study,
Nearest to found: lost, study, lake,
Nearest to found: lost, study, lake, determine,
Nearest to found: lost, study, lake, determine, ray,
Nearest to found: lost, study, lake, determine, ray, tear,
Nearest to found: lost, study, lake, determine, ray, tear, floor,
Nearest to found: lost, study, lake, determine, ray, tear, floor, chloride,
Nearest to used: statics,
Nearest to used: statics, cee,
Nearest to used: statics, cee, finish,
Nearest to used: statics, cee, finish, various,
Nearest to used: statics, cee, finish, various, eef,
Nearest to used: statics, cee, finish, various, eef, disc,
Nearest to used: statics, cee, finish, various, eef, disc, cross,
Nearest to used: statics, cee, finish, various, eef, disc, cross, download,
Nearest to airport: soccer,
Nearest to airport: soccer, thursday,
Nearest to airport: soccer, thursday, acer,
Nearest to airport: soccer, thursday, acer, block,
Nearest to airport: soccer, thursday, acer, block, fdaaa,
Nearest to airport: soccer, thursday, acer, block, fdaaa, took,
Nearest to airport: soccer, thursday, acer, block, fdaaa, took, edbb,
Nearest to airport: soccer, thursday, acer, block, fdaaa, took, edbb, changed,
Nearest to pm: generic,
Nearest to pm: generic, dbded,
Nearest to pm: generic, dbded, morning,
Nearest to pm: generic, dbded, morning, rotation,
Nearest to pm: generic, dbded, morning, rotation, language,
Nearest to pm: generic, dbded, morning, rotation, language, crosby,
Nearest to pm: generic, dbded, morning, rotation, language, crosby, towards,
Nearest to pm: generic, dbded, morning, rotation, language, crosby, towards, grade,
Nearest to underline: anything,
Nearest to underline: anything, bad,
Nearest to underline: anything, bad, eea,
Nearest to underline: anything, bad, eea, often,
Nearest to underline: anything, bad, eea, often, ab,
Nearest to underline: anything, bad, eea, often, ab, august,
Nearest to underline: anything, bad, eea, often, ab, august, intro,
Nearest to underline: anything, bad, eea, often, ab, august, intro, e,
Nearest to percopo: prepare,
Nearest to percopo: prepare, pockets,
Nearest to percopo: prepare, pockets, jpg,
Nearest to percopo: prepare, pockets, jpg, avenue,
Nearest to percopo: prepare, pockets, jpg, avenue, retirement,
Nearest to percopo: prepare, pockets, jpg, avenue, retirement, missing,
Nearest to percopo: prepare, pockets, jpg, avenue, retirement, missing, along,
Nearest to percopo: prepare, pockets, jpg, avenue, retirement, missing, along, broke,
Nearest to div: couponing,
Nearest to div: couponing, hosting,
Nearest to div: couponing, hosting, eec,
Nearest to div: couponing, hosting, eec, ends,
Nearest to div: couponing, hosting, eec, ends, e,
Nearest to div: couponing, hosting, eec, ends, e, bd,
Nearest to div: couponing, hosting, eec, ends, e, bd, li,
Nearest to div: couponing, hosting, eec, ends, e, bd, li, steps,
Nearest to externalclass: externalclassf,
Nearest to externalclass: externalclassf, fcb,
Nearest to externalclass: externalclassf, fcb, bab,
Nearest to externalclass: externalclassf, fcb, bab, margin,
Nearest to externalclass: externalclassf, fcb, bab, margin, ee,
Nearest to externalclass: externalclassf, fcb, bab, margin, ee, afa,
Nearest to externalclass: externalclassf, fcb, bab, margin, ee, afa, eec,
Nearest to externalclass: externalclassf, fcb, bab, margin, ee, afa, eec, dbded,
Nearest to free: externalclasscfbded,
Nearest to free: externalclasscfbded, resolution,
Nearest to free: externalclasscfbded, resolution, windows,
Nearest to free: externalclasscfbded, resolution, windows, returned,
Nearest to free: externalclasscfbded, resolution, windows, returned, cbe,
Nearest to free: externalclasscfbded, resolution, windows, returned, cbe, fcb,
Nearest to free: externalclasscfbded, resolution, windows, returned, cbe, fcb, return,
Nearest to free: externalclasscfbded, resolution, windows, returned, cbe, fcb, return, wellness,
Nearest to margin: externalclasscfbded,
Nearest to margin: externalclasscfbded, fcb,
Nearest to margin: externalclasscfbded, fcb, dorm,
Nearest to margin: externalclasscfbded, fcb, dorm, thesis,
Nearest to margin: externalclasscfbded, fcb, dorm, thesis, externalclass,
Nearest to margin: externalclasscfbded, fcb, dorm, thesis, externalclass, afa,
Nearest to margin: externalclasscfbded, fcb, dorm, thesis, externalclass, afa, biology,
Nearest to margin: externalclasscfbded, fcb, dorm, thesis, externalclass, afa, biology, easily,
Average loss at step  12000 :  3.5742196238
Average loss at step  14000 :  3.49751707268
Average loss at step  16000 :  3.45453358489
Average loss at step  18000 :  3.42691146111
Average loss at step  20000 :  3.34691510367
Nearest to family: theta,
Nearest to family: theta, sans,
Nearest to family: theta, sans, business,
Nearest to family: theta, sans, business, latest,
Nearest to family: theta, sans, business, latest, station,
Nearest to family: theta, sans, business, latest, station, interaction,
Nearest to family: theta, sans, business, latest, station, interaction, mounting,
Nearest to family: theta, sans, business, latest, station, interaction, mounting, therapy,
Nearest to engineering: mark,
Nearest to engineering: mark, functions,
Nearest to engineering: mark, functions, management,
Nearest to engineering: mark, functions, management, flag,
Nearest to engineering: mark, functions, management, flag, ead,
Nearest to engineering: mark, functions, management, flag, ead, statistics,
Nearest to engineering: mark, functions, management, flag, ead, statistics, academics,
Nearest to engineering: mark, functions, management, flag, ead, statistics, academics, saddle,
Nearest to serif: f,
Nearest to serif: f, underline,
Nearest to serif: f, underline, dbded,
Nearest to serif: f, underline, dbded, onto,
Nearest to serif: f, underline, dbded, onto, field,
Nearest to serif: f, underline, dbded, onto, field, msonormal,
Nearest to serif: f, underline, dbded, onto, field, msonormal, bf,
Nearest to serif: f, underline, dbded, onto, field, msonormal, bf, button,
Nearest to help: vga,
Nearest to help: vga, developers,
Nearest to help: vga, developers, appreciate,
Nearest to help: vga, developers, appreciate, sounds,
Nearest to help: vga, developers, appreciate, sounds, questions,
Nearest to help: vga, developers, appreciate, sounds, questions, louis,
Nearest to help: vga, developers, appreciate, sounds, questions, louis, intramurals,
Nearest to help: vga, developers, appreciate, sounds, questions, louis, intramurals, sunglasses,
Nearest to cell: UNK,
Nearest to cell: UNK, imgur,
Nearest to cell: UNK, imgur, vacuum,
Nearest to cell: UNK, imgur, vacuum, andrew,
Nearest to cell: UNK, imgur, vacuum, andrew, solving,
Nearest to cell: UNK, imgur, vacuum, andrew, solving, fell,
Nearest to cell: UNK, imgur, vacuum, andrew, solving, fell, clicking,
Nearest to cell: UNK, imgur, vacuum, andrew, solving, fell, clicking, src,
Nearest to know: hold,
Nearest to know: hold, anna,
Nearest to know: hold, anna, flat,
Nearest to know: hold, anna, flat, safe,
Nearest to know: hold, anna, flat, safe, hare,
Nearest to know: hold, anna, flat, safe, hare, ben,
Nearest to know: hold, anna, flat, safe, hare, ben, tell,
Nearest to know: hold, anna, flat, safe, hare, ben, tell, jack,
Nearest to found: lost,
Nearest to found: lost, left,
Nearest to found: lost, left, lake,
Nearest to found: lost, left, lake, floor,
Nearest to found: lost, left, lake, floor, missing,
Nearest to found: lost, left, lake, floor, missing, nike,
Nearest to found: lost, left, lake, floor, missing, nike, hall,
Nearest to found: lost, left, lake, floor, missing, nike, hall, tear,
Nearest to used: statics,
Nearest to used: statics, various,
Nearest to used: statics, various, finish,
Nearest to used: statics, various, finish, cee,
Nearest to used: statics, various, finish, cee, eef,
Nearest to used: statics, various, finish, cee, eef, cross,
Nearest to used: statics, various, finish, cee, eef, cross, br,
Nearest to used: statics, various, finish, cee, eef, cross, br, fellow,
Nearest to airport: soccer,
Nearest to airport: soccer, thursday,
Nearest to airport: soccer, thursday, acer,
Nearest to airport: soccer, thursday, acer, fdaaa,
Nearest to airport: soccer, thursday, acer, fdaaa, took,
Nearest to airport: soccer, thursday, acer, fdaaa, took, block,
Nearest to airport: soccer, thursday, acer, fdaaa, took, block, changed,
Nearest to airport: soccer, thursday, acer, fdaaa, took, block, changed, alzheimer,
Nearest to pm: morning,
Nearest to pm: morning, generic,
Nearest to pm: morning, generic, dbded,
Nearest to pm: morning, generic, dbded, crosby,
Nearest to pm: morning, generic, dbded, crosby, tahoma,
Nearest to pm: morning, generic, dbded, crosby, tahoma, grade,
Nearest to pm: morning, generic, dbded, crosby, tahoma, grade, language,
Nearest to pm: morning, generic, dbded, crosby, tahoma, grade, language, rotation,
Nearest to underline: msonormal,
Nearest to underline: msonormal, serif,
Nearest to underline: msonormal, serif, anything,
Nearest to underline: msonormal, serif, anything, august,
Nearest to underline: msonormal, serif, anything, august, eea,
Nearest to underline: msonormal, serif, anything, august, eea, bad,
Nearest to underline: msonormal, serif, anything, august, eea, bad, c,
Nearest to underline: msonormal, serif, anything, august, eea, bad, c, often,
Nearest to percopo: prepare,
Nearest to percopo: prepare, pockets,
Nearest to percopo: prepare, pockets, jpg,
Nearest to percopo: prepare, pockets, jpg, task,
Nearest to percopo: prepare, pockets, jpg, task, internal,
Nearest to percopo: prepare, pockets, jpg, task, internal, deck,
Nearest to percopo: prepare, pockets, jpg, task, internal, deck, retirement,
Nearest to percopo: prepare, pockets, jpg, task, internal, deck, retirement, basics,
Nearest to div: li,
Nearest to div: li, b,
Nearest to div: li, b, couponing,
Nearest to div: li, b, couponing, hosting,
Nearest to div: li, b, couponing, hosting, eec,
Nearest to div: li, b, couponing, hosting, eec, ends,
Nearest to div: li, b, couponing, hosting, eec, ends, aba,
Nearest to div: li, b, couponing, hosting, eec, ends, aba, bd,
Nearest to externalclass: externalclassf,
Nearest to externalclass: externalclassf, fcb,
Nearest to externalclass: externalclassf, fcb, externalclasscfbded,
Nearest to externalclass: externalclassf, fcb, externalclasscfbded, bab,
Nearest to externalclass: externalclassf, fcb, externalclasscfbded, bab, f,
Nearest to externalclass: externalclassf, fcb, externalclasscfbded, bab, f, margin,
Nearest to externalclass: externalclassf, fcb, externalclasscfbded, bab, f, margin, afa,
Nearest to externalclass: externalclassf, fcb, externalclasscfbded, bab, f, margin, afa, fbc,
Nearest to free: externalclasscfbded,
Nearest to free: externalclasscfbded, resolution,
Nearest to free: externalclasscfbded, resolution, cbe,
Nearest to free: externalclasscfbded, resolution, cbe, windows,
Nearest to free: externalclasscfbded, resolution, cbe, windows, returned,
Nearest to free: externalclasscfbded, resolution, cbe, windows, returned, wellness,
Nearest to free: externalclasscfbded, resolution, cbe, windows, returned, wellness, listing,
Nearest to free: externalclasscfbded, resolution, cbe, windows, returned, wellness, listing, return,
Nearest to margin: externalclasscfbded,
Nearest to margin: externalclasscfbded, dorm,
Nearest to margin: externalclasscfbded, dorm, externalclass,
Nearest to margin: externalclasscfbded, dorm, externalclass, thesis,
Nearest to margin: externalclasscfbded, dorm, externalclass, thesis, fcb,
Nearest to margin: externalclasscfbded, dorm, externalclass, thesis, fcb, top,
Nearest to margin: externalclasscfbded, dorm, externalclass, thesis, fcb, top, drivers,
Nearest to margin: externalclasscfbded, dorm, externalclass, thesis, fcb, top, drivers, easily,
Average loss at step  22000 :  3.33023425996
Average loss at step  24000 :  3.310354334
Average loss at step  26000 :  3.24996370226
Average loss at step  28000 :  3.23306220457
Average loss at step  30000 :  3.24601641995
Nearest to family: theta,
Nearest to family: theta, latest,
Nearest to family: theta, latest, business,
Nearest to family: theta, latest, business, sans,
Nearest to family: theta, latest, business, sans, station,
Nearest to family: theta, latest, business, sans, station, interaction,
Nearest to family: theta, latest, business, sans, station, interaction, mounting,
Nearest to family: theta, latest, business, sans, station, interaction, mounting, therapy,
Nearest to engineering: mark,
Nearest to engineering: mark, functions,
Nearest to engineering: mark, functions, management,
Nearest to engineering: mark, functions, management, saddle,
Nearest to engineering: mark, functions, management, saddle, academics,
Nearest to engineering: mark, functions, management, saddle, academics, statistics,
Nearest to engineering: mark, functions, management, saddle, academics, statistics, ead,
Nearest to engineering: mark, functions, management, saddle, academics, statistics, ead, eec,
Nearest to serif: underline,
Nearest to serif: underline, msonormal,
Nearest to serif: underline, msonormal, dbded,
Nearest to serif: underline, msonormal, dbded, f,
Nearest to serif: underline, msonormal, dbded, f, onto,
Nearest to serif: underline, msonormal, dbded, f, onto, bf,
Nearest to serif: underline, msonormal, dbded, f, onto, bf, windowtext,
Nearest to serif: underline, msonormal, dbded, f, onto, bf, windowtext, field,
Nearest to help: developers,
Nearest to help: developers, intramurals,
Nearest to help: developers, intramurals, appreciate,
Nearest to help: developers, intramurals, appreciate, louis,
Nearest to help: developers, intramurals, appreciate, louis, questions,
Nearest to help: developers, intramurals, appreciate, louis, questions, vga,
Nearest to help: developers, intramurals, appreciate, louis, questions, vga, sounds,
Nearest to help: developers, intramurals, appreciate, louis, questions, vga, sounds, power,
Nearest to cell: imgur,
Nearest to cell: imgur, solving,
Nearest to cell: imgur, solving, fell,
Nearest to cell: imgur, solving, fell, andrew,
Nearest to cell: imgur, solving, fell, andrew, vacuum,
Nearest to cell: imgur, solving, fell, andrew, vacuum, buying,
Nearest to cell: imgur, solving, fell, andrew, vacuum, buying, clicking,
Nearest to cell: imgur, solving, fell, andrew, vacuum, buying, clicking, circle,
Nearest to know: hold,
Nearest to know: hold, anna,
Nearest to know: hold, anna, tell,
Nearest to know: hold, anna, tell, safe,
Nearest to know: hold, anna, tell, safe, hare,
Nearest to know: hold, anna, tell, safe, hare, ben,
Nearest to know: hold, anna, tell, safe, hare, ben, rush,
Nearest to know: hold, anna, tell, safe, hare, ben, rush, flat,
Nearest to found: lost,
Nearest to found: lost, floor,
Nearest to found: lost, floor, left,
Nearest to found: lost, floor, left, nike,
Nearest to found: lost, floor, left, nike, hall,
Nearest to found: lost, floor, left, nike, hall, kepchaja,
Nearest to found: lost, floor, left, nike, hall, kepchaja, lake,
Nearest to found: lost, floor, left, nike, hall, kepchaja, lake, missing,
Nearest to used: statics,
Nearest to used: statics, various,
Nearest to used: statics, various, finish,
Nearest to used: statics, various, finish, eef,
Nearest to used: statics, various, finish, eef, cee,
Nearest to used: statics, various, finish, eef, cee, cross,
Nearest to used: statics, various, finish, eef, cee, cross, wall,
Nearest to used: statics, various, finish, eef, cee, cross, wall, exercise,
Nearest to airport: soccer,
Nearest to airport: soccer, fdaaa,
Nearest to airport: soccer, fdaaa, thursday,
Nearest to airport: soccer, fdaaa, thursday, acer,
Nearest to airport: soccer, fdaaa, thursday, acer, took,
Nearest to airport: soccer, fdaaa, thursday, acer, took, aaef,
Nearest to airport: soccer, fdaaa, thursday, acer, took, aaef, block,
Nearest to airport: soccer, fdaaa, thursday, acer, took, aaef, block, edb,
Nearest to pm: morning,
Nearest to pm: morning, grade,
Nearest to pm: morning, grade, generic,
Nearest to pm: morning, grade, generic, crosby,
Nearest to pm: morning, grade, generic, crosby, tahoma,
Nearest to pm: morning, grade, generic, crosby, tahoma, dbded,
Nearest to pm: morning, grade, generic, crosby, tahoma, dbded, sunday,
Nearest to pm: morning, grade, generic, crosby, tahoma, dbded, sunday, village,
Nearest to underline: msonormal,
Nearest to underline: msonormal, serif,
Nearest to underline: msonormal, serif, august,
Nearest to underline: msonormal, serif, august, anything,
Nearest to underline: msonormal, serif, august, anything, windowtext,
Nearest to underline: msonormal, serif, august, anything, windowtext, eea,
Nearest to underline: msonormal, serif, august, anything, windowtext, eea, sans,
Nearest to underline: msonormal, serif, august, anything, windowtext, eea, sans, dbded,
Nearest to percopo: prepare,
Nearest to percopo: prepare, pockets,
Nearest to percopo: prepare, pockets, deck,
Nearest to percopo: prepare, pockets, deck, lakeside,
Nearest to percopo: prepare, pockets, deck, lakeside, task,
Nearest to percopo: prepare, pockets, deck, lakeside, task, internal,
Nearest to percopo: prepare, pockets, deck, lakeside, task, internal, jpg,
Nearest to percopo: prepare, pockets, deck, lakeside, task, internal, jpg, retirement,
Nearest to div: li,
Nearest to div: li, b,
Nearest to div: li, b, msochpdefault,
Nearest to div: li, b, msochpdefault, eec,
Nearest to div: li, b, msochpdefault, eec, couponing,
Nearest to div: li, b, msochpdefault, eec, couponing, hosting,
Nearest to div: li, b, msochpdefault, eec, couponing, hosting, bd,
Nearest to div: li, b, msochpdefault, eec, couponing, hosting, bd, ends,
Nearest to externalclass: externalclassf,
Nearest to externalclass: externalclassf, externalclasscfbded,
Nearest to externalclass: externalclassf, externalclasscfbded, fcb,
Nearest to externalclass: externalclassf, externalclasscfbded, fcb, f,
Nearest to externalclass: externalclassf, externalclasscfbded, fcb, f, bab,
Nearest to externalclass: externalclassf, externalclasscfbded, fcb, f, bab, b,
Nearest to externalclass: externalclassf, externalclasscfbded, fcb, f, bab, b, fbc,
Nearest to externalclass: externalclassf, externalclasscfbded, fcb, f, bab, b, fbc, externalclassdf,
Nearest to free: resolution,
Nearest to free: resolution, cbe,
Nearest to free: resolution, cbe, returned,
Nearest to free: resolution, cbe, returned, externalclasscfbded,
Nearest to free: resolution, cbe, returned, externalclasscfbded, windows,
Nearest to free: resolution, cbe, returned, externalclasscfbded, windows, clear,
Nearest to free: resolution, cbe, returned, externalclasscfbded, windows, clear, wellness,
Nearest to free: resolution, cbe, returned, externalclasscfbded, windows, clear, wellness, bluetooth,
Nearest to margin: externalclasscfbded,
Nearest to margin: externalclasscfbded, dorm,
Nearest to margin: externalclasscfbded, dorm, top,
Nearest to margin: externalclasscfbded, dorm, top, externalclass,
Nearest to margin: externalclasscfbded, dorm, top, externalclass, drivers,
Nearest to margin: externalclasscfbded, dorm, top, externalclass, drivers, easily,
Nearest to margin: externalclasscfbded, dorm, top, externalclass, drivers, easily, bottom,
Nearest to margin: externalclasscfbded, dorm, top, externalclass, drivers, easily, bottom, thesis,
Average loss at step  32000 :  3.18468966526
Average loss at step  34000 :  3.18632279354
Average loss at step  36000 :  3.14601511568
Average loss at step  38000 :  3.1408300035
Average loss at step  40000 :  3.11276617932
Nearest to family: theta,
Nearest to family: theta, latest,
Nearest to family: theta, latest, station,
Nearest to family: theta, latest, station, business,
Nearest to family: theta, latest, station, business, sans,
Nearest to family: theta, latest, station, business, sans, audrey,
Nearest to family: theta, latest, station, business, sans, audrey, therapy,
Nearest to family: theta, latest, station, business, sans, audrey, therapy, interaction,
Nearest to engineering: mark,
Nearest to engineering: mark, functions,
Nearest to engineering: mark, functions, saddle,
Nearest to engineering: mark, functions, saddle, principles,
Nearest to engineering: mark, functions, saddle, principles, management,
Nearest to engineering: mark, functions, saddle, principles, management, applied,
Nearest to engineering: mark, functions, saddle, principles, management, applied, academics,
Nearest to engineering: mark, functions, saddle, principles, management, applied, academics, statistics,
Nearest to serif: underline,
Nearest to serif: underline, msonormal,
Nearest to serif: underline, msonormal, dbded,
Nearest to serif: underline, msonormal, dbded, windowtext,
Nearest to serif: underline, msonormal, dbded, windowtext, bf,
Nearest to serif: underline, msonormal, dbded, windowtext, bf, onto,
Nearest to serif: underline, msonormal, dbded, windowtext, bf, onto, b,
Nearest to serif: underline, msonormal, dbded, windowtext, bf, onto, b, field,
Nearest to help: developers,
Nearest to help: developers, intramurals,
Nearest to help: developers, intramurals, louis,
Nearest to help: developers, intramurals, louis, appreciate,
Nearest to help: developers, intramurals, louis, appreciate, power,
Nearest to help: developers, intramurals, louis, appreciate, power, millerna,
Nearest to help: developers, intramurals, louis, appreciate, power, millerna, reading,
Nearest to help: developers, intramurals, louis, appreciate, power, millerna, reading, environment,
Nearest to cell: imgur,
Nearest to cell: imgur, solving,
Nearest to cell: imgur, solving, fell,
Nearest to cell: imgur, solving, fell, buying,
Nearest to cell: imgur, solving, fell, buying, UNK,
Nearest to cell: imgur, solving, fell, buying, UNK, vacuum,
Nearest to cell: imgur, solving, fell, buying, UNK, vacuum, surveymonkey,
Nearest to cell: imgur, solving, fell, buying, UNK, vacuum, surveymonkey, circle,
Nearest to know: hold,
Nearest to know: hold, anna,
Nearest to know: hold, anna, tell,
Nearest to know: hold, anna, tell, ben,
Nearest to know: hold, anna, tell, ben, safe,
Nearest to know: hold, anna, tell, ben, safe, fafsa,
Nearest to know: hold, anna, tell, ben, safe, fafsa, cookies,
Nearest to know: hold, anna, tell, ben, safe, fafsa, cookies, rush,
Nearest to found: lost,
Nearest to found: lost, nike,
Nearest to found: lost, nike, floor,
Nearest to found: lost, nike, floor, left,
Nearest to found: lost, nike, floor, left, kepchaja,
Nearest to found: lost, nike, floor, left, kepchaja, hall,
Nearest to found: lost, nike, floor, left, kepchaja, hall, lake,
Nearest to found: lost, nike, floor, left, kepchaja, hall, lake, believe,
Nearest to used: statics,
Nearest to used: statics, various,
Nearest to used: statics, various, finish,
Nearest to used: statics, various, finish, eef,
Nearest to used: statics, various, finish, eef, environment,
Nearest to used: statics, various, finish, eef, environment, recreation,
Nearest to used: statics, various, finish, eef, environment, recreation, wall,
Nearest to used: statics, various, finish, eef, environment, recreation, wall, cross,
Nearest to airport: soccer,
Nearest to airport: soccer, fdaaa,
Nearest to airport: soccer, fdaaa, acer,
Nearest to airport: soccer, fdaaa, acer, thursday,
Nearest to airport: soccer, fdaaa, acer, thursday, monday,
Nearest to airport: soccer, fdaaa, acer, thursday, monday, edb,
Nearest to airport: soccer, fdaaa, acer, thursday, monday, edb, sep,
Nearest to airport: soccer, fdaaa, acer, thursday, monday, edb, sep, indy,
Nearest to pm: morning,
Nearest to pm: morning, crosby,
Nearest to pm: morning, crosby, grade,
Nearest to pm: morning, crosby, grade, tahoma,
Nearest to pm: morning, crosby, grade, tahoma, generic,
Nearest to pm: morning, crosby, grade, tahoma, generic, flight,
Nearest to pm: morning, crosby, grade, tahoma, generic, flight, p,
Nearest to pm: morning, crosby, grade, tahoma, generic, flight, p, leave,
Nearest to underline: msonormal,
Nearest to underline: msonormal, serif,
Nearest to underline: msonormal, serif, windowtext,
Nearest to underline: msonormal, serif, windowtext, august,
Nearest to underline: msonormal, serif, windowtext, august, anything,
Nearest to underline: msonormal, serif, windowtext, august, anything, b,
Nearest to underline: msonormal, serif, windowtext, august, anything, b, eea,
Nearest to underline: msonormal, serif, windowtext, august, anything, b, eea, sans,
Nearest to percopo: prepare,
Nearest to percopo: prepare, lakeside,
Nearest to percopo: prepare, lakeside, deck,
Nearest to percopo: prepare, lakeside, deck, pockets,
Nearest to percopo: prepare, lakeside, deck, pockets, task,
Nearest to percopo: prepare, lakeside, deck, pockets, task, retirement,
Nearest to percopo: prepare, lakeside, deck, pockets, task, retirement, jpg,
Nearest to percopo: prepare, lakeside, deck, pockets, task, retirement, jpg, internal,
Nearest to div: li,
Nearest to div: li, b,
Nearest to div: li, b, msochpdefault,
Nearest to div: li, b, msochpdefault, eec,
Nearest to div: li, b, msochpdefault, eec, span,
Nearest to div: li, b, msochpdefault, eec, span, externalclasscfbded,
Nearest to div: li, b, msochpdefault, eec, span, externalclasscfbded, couponing,
Nearest to div: li, b, msochpdefault, eec, span, externalclasscfbded, couponing, eb,
Nearest to externalclass: externalclasscfbded,
Nearest to externalclass: externalclasscfbded, externalclassf,
Nearest to externalclass: externalclasscfbded, externalclassf, fcb,
Nearest to externalclass: externalclasscfbded, externalclassf, fcb, c,
Nearest to externalclass: externalclasscfbded, externalclassf, fcb, c, externalclassdf,
Nearest to externalclass: externalclasscfbded, externalclassf, fcb, c, externalclassdf, ebebc,
Nearest to externalclass: externalclasscfbded, externalclassf, fcb, c, externalclassdf, ebebc, b,
Nearest to externalclass: externalclasscfbded, externalclassf, fcb, c, externalclassdf, ebebc, b, bab,
Nearest to free: clear,
Nearest to free: clear, resolution,
Nearest to free: clear, resolution, returned,
Nearest to free: clear, resolution, returned, cbe,
Nearest to free: clear, resolution, returned, cbe, bluetooth,
Nearest to free: clear, resolution, returned, cbe, bluetooth, windows,
Nearest to free: clear, resolution, returned, cbe, bluetooth, windows, wellness,
Nearest to free: clear, resolution, returned, cbe, bluetooth, windows, wellness, listing,
Nearest to margin: externalclasscfbded,
Nearest to margin: externalclasscfbded, dorm,
Nearest to margin: externalclasscfbded, dorm, top,
Nearest to margin: externalclasscfbded, dorm, top, externalclass,
Nearest to margin: externalclasscfbded, dorm, top, externalclass, drivers,
Nearest to margin: externalclasscfbded, dorm, top, externalclass, drivers, sleeping,
Nearest to margin: externalclasscfbded, dorm, top, externalclass, drivers, sleeping, easily,
Nearest to margin: externalclasscfbded, dorm, top, externalclass, drivers, sleeping, easily, bottom,
Average loss at step  42000 :  3.11690880585
Average loss at step  44000 :  3.14218918645
Average loss at step  46000 :  3.06256911141
Average loss at step  48000 :  3.06674993843
Average loss at step  50000 :  3.06553870565
Nearest to family: theta,
Nearest to family: theta, latest,
Nearest to family: theta, latest, station,
Nearest to family: theta, latest, station, business,
Nearest to family: theta, latest, station, business, audrey,
Nearest to family: theta, latest, station, business, audrey, sans,
Nearest to family: theta, latest, station, business, audrey, sans, c,
Nearest to family: theta, latest, station, business, audrey, sans, c, interaction,
Nearest to engineering: mark,
Nearest to engineering: mark, saddle,
Nearest to engineering: mark, saddle, applied,
Nearest to engineering: mark, saddle, applied, principles,
Nearest to engineering: mark, saddle, applied, principles, management,
Nearest to engineering: mark, saddle, applied, principles, management, functions,
Nearest to engineering: mark, saddle, applied, principles, management, functions, academics,
Nearest to engineering: mark, saddle, applied, principles, management, functions, academics, graduate,
Nearest to serif: underline,
Nearest to serif: underline, msonormal,
Nearest to serif: underline, msonormal, f,
Nearest to serif: underline, msonormal, f, windowtext,
Nearest to serif: underline, msonormal, f, windowtext, c,
Nearest to serif: underline, msonormal, f, windowtext, c, b,
Nearest to serif: underline, msonormal, f, windowtext, c, b, dbded,
Nearest to serif: underline, msonormal, f, windowtext, c, b, dbded, bf,
Nearest to help: intramurals,
Nearest to help: intramurals, developers,
Nearest to help: intramurals, developers, someone,
Nearest to help: intramurals, developers, someone, reading,
Nearest to help: intramurals, developers, someone, reading, louis,
Nearest to help: intramurals, developers, someone, reading, louis, millerna,
Nearest to help: intramurals, developers, someone, reading, louis, millerna, power,
Nearest to help: intramurals, developers, someone, reading, louis, millerna, power, fun,
Nearest to cell: imgur,
Nearest to cell: imgur, solving,
Nearest to cell: imgur, solving, UNK,
Nearest to cell: imgur, solving, UNK, buying,
Nearest to cell: imgur, solving, UNK, buying, fell,
Nearest to cell: imgur, solving, UNK, buying, fell, claimed,
Nearest to cell: imgur, solving, UNK, buying, fell, claimed, surveymonkey,
Nearest to cell: imgur, solving, UNK, buying, fell, claimed, surveymonkey, step,
Nearest to know: hold,
Nearest to know: hold, anna,
Nearest to know: hold, anna, tell,
Nearest to know: hold, anna, tell, ben,
Nearest to know: hold, anna, tell, ben, fafsa,
Nearest to know: hold, anna, tell, ben, fafsa, safe,
Nearest to know: hold, anna, tell, ben, fafsa, safe, cookies,
Nearest to know: hold, anna, tell, ben, fafsa, safe, cookies, rush,
Nearest to found: lost,
Nearest to found: lost, nike,
Nearest to found: lost, nike, kepchaja,
Nearest to found: lost, nike, kepchaja, seen,
Nearest to found: lost, nike, kepchaja, seen, floor,
Nearest to found: lost, nike, kepchaja, seen, floor, sometime,
Nearest to found: lost, nike, kepchaja, seen, floor, sometime, madness,
Nearest to found: lost, nike, kepchaja, seen, floor, sometime, madness, left,
Nearest to used: statics,
Nearest to used: statics, various,
Nearest to used: statics, various, environment,
Nearest to used: statics, various, environment, finish,
Nearest to used: statics, various, environment, finish, eef,
Nearest to used: statics, various, environment, finish, eef, location,
Nearest to used: statics, various, environment, finish, eef, location, recreation,
Nearest to used: statics, various, environment, finish, eef, location, recreation, audrey,
Nearest to airport: soccer,
Nearest to airport: soccer, fdaaa,
Nearest to airport: soccer, fdaaa, edb,
Nearest to airport: soccer, fdaaa, edb, indy,
Nearest to airport: soccer, fdaaa, edb, indy, sep,
Nearest to airport: soccer, fdaaa, edb, indy, sep, monday,
Nearest to airport: soccer, fdaaa, edb, indy, sep, monday, arriving,
Nearest to airport: soccer, fdaaa, edb, indy, sep, monday, arriving, adc,
Nearest to pm: morning,
Nearest to pm: morning, grade,
Nearest to pm: morning, grade, crosby,
Nearest to pm: morning, grade, crosby, tahoma,
Nearest to pm: morning, grade, crosby, tahoma, p,
Nearest to pm: morning, grade, crosby, tahoma, p, category,
Nearest to pm: morning, grade, crosby, tahoma, p, category, arrives,
Nearest to pm: morning, grade, crosby, tahoma, p, category, arrives, flight,
Nearest to underline: msonormal,
Nearest to underline: msonormal, serif,
Nearest to underline: msonormal, serif, b,
Nearest to underline: msonormal, serif, b, windowtext,
Nearest to underline: msonormal, serif, b, windowtext, e,
Nearest to underline: msonormal, serif, b, windowtext, e, august,
Nearest to underline: msonormal, serif, b, windowtext, e, august, sans,
Nearest to underline: msonormal, serif, b, windowtext, e, august, sans, fd,
Nearest to percopo: lakeside,
Nearest to percopo: lakeside, prepare,
Nearest to percopo: lakeside, prepare, deck,
Nearest to percopo: lakeside, prepare, deck, pockets,
Nearest to percopo: lakeside, prepare, deck, pockets, task,
Nearest to percopo: lakeside, prepare, deck, pockets, task, retirement,
Nearest to percopo: lakeside, prepare, deck, pockets, task, retirement, jpg,
Nearest to percopo: lakeside, prepare, deck, pockets, task, retirement, jpg, war,
Nearest to div: li,
Nearest to div: li, msochpdefault,
Nearest to div: li, msochpdefault, span,
Nearest to div: li, msochpdefault, span, b,
Nearest to div: li, msochpdefault, span, b, eec,
Nearest to div: li, msochpdefault, span, b, eec, couponing,
Nearest to div: li, msochpdefault, span, b, eec, couponing, bd,
Nearest to div: li, msochpdefault, span, b, eec, couponing, bd, ends,
Nearest to externalclass: externalclasscfbded,
Nearest to externalclass: externalclasscfbded, externalclassf,
Nearest to externalclass: externalclasscfbded, externalclassf, b,
Nearest to externalclass: externalclasscfbded, externalclassf, b, ebebc,
Nearest to externalclass: externalclasscfbded, externalclassf, b, ebebc, c,
Nearest to externalclass: externalclasscfbded, externalclassf, b, ebebc, c, fdaaa,
Nearest to externalclass: externalclasscfbded, externalclassf, b, ebebc, c, fdaaa, ddd,
Nearest to externalclass: externalclasscfbded, externalclassf, b, ebebc, c, fdaaa, ddd, e,
Nearest to free: clear,
Nearest to free: clear, cbe,
Nearest to free: clear, cbe, resolution,
Nearest to free: clear, cbe, resolution, returned,
Nearest to free: clear, cbe, resolution, returned, bluetooth,
Nearest to free: clear, cbe, resolution, returned, bluetooth, wellness,
Nearest to free: clear, cbe, resolution, returned, bluetooth, wellness, instead,
Nearest to free: clear, cbe, resolution, returned, bluetooth, wellness, instead, windows,
Nearest to margin: externalclasscfbded,
Nearest to margin: externalclasscfbded, sleeping,
Nearest to margin: externalclasscfbded, sleeping, top,
Nearest to margin: externalclasscfbded, sleeping, top, dorm,
Nearest to margin: externalclasscfbded, sleeping, top, dorm, drivers,
Nearest to margin: externalclasscfbded, sleeping, top, dorm, drivers, easily,
Nearest to margin: externalclasscfbded, sleeping, top, dorm, drivers, easily, externalclass,
Nearest to margin: externalclasscfbded, sleeping, top, dorm, drivers, easily, externalclass, pt,
Average loss at step  52000 :  3.03798307073
Average loss at step  54000 :  3.03076866671
Average loss at step  56000 :  3.04034351477
Average loss at step  58000 :  2.99386148727
Average loss at step  60000 :  3.00851644897
Nearest to family: theta,
Nearest to family: theta, latest,
Nearest to family: theta, latest, station,
Nearest to family: theta, latest, station, audrey,
Nearest to family: theta, latest, station, audrey, business,
Nearest to family: theta, latest, station, audrey, business, interaction,
Nearest to family: theta, latest, station, audrey, business, interaction, kroger,
Nearest to family: theta, latest, station, audrey, business, interaction, kroger, decoration,
Nearest to engineering: saddle,
Nearest to engineering: saddle, applied,
Nearest to engineering: saddle, applied, principles,
Nearest to engineering: saddle, applied, principles, academics,
Nearest to engineering: saddle, applied, principles, academics, mark,
Nearest to engineering: saddle, applied, principles, academics, mark, graduate,
Nearest to engineering: saddle, applied, principles, academics, mark, graduate, statistics,
Nearest to engineering: saddle, applied, principles, academics, mark, graduate, statistics, management,
Nearest to serif: underline,
Nearest to serif: underline, msonormal,
Nearest to serif: underline, msonormal, f,
Nearest to serif: underline, msonormal, f, c,
Nearest to serif: underline, msonormal, f, c, windowtext,
Nearest to serif: underline, msonormal, f, c, windowtext, bf,
Nearest to serif: underline, msonormal, f, c, windowtext, bf, dbded,
Nearest to serif: underline, msonormal, f, c, windowtext, bf, dbded, onto,
Nearest to help: intramurals,
Nearest to help: intramurals, developers,
Nearest to help: intramurals, developers, someone,
Nearest to help: intramurals, developers, someone, reading,
Nearest to help: intramurals, developers, someone, reading, millerna,
Nearest to help: intramurals, developers, someone, reading, millerna, louis,
Nearest to help: intramurals, developers, someone, reading, millerna, louis, fun,
Nearest to help: intramurals, developers, someone, reading, millerna, louis, fun, power,
Nearest to cell: imgur,
Nearest to cell: imgur, solving,
Nearest to cell: imgur, solving, buying,
Nearest to cell: imgur, solving, buying, fell,
Nearest to cell: imgur, solving, buying, fell, claimed,
Nearest to cell: imgur, solving, buying, fell, claimed, step,
Nearest to cell: imgur, solving, buying, fell, claimed, step, clicking,
Nearest to cell: imgur, solving, buying, fell, claimed, step, clicking, surveymonkey,
Nearest to know: hold,
Nearest to know: hold, tell,
Nearest to know: hold, tell, anna,
Nearest to know: hold, tell, anna, fafsa,
Nearest to know: hold, tell, anna, fafsa, ben,
Nearest to know: hold, tell, anna, fafsa, ben, cookies,
Nearest to know: hold, tell, anna, fafsa, ben, cookies, safe,
Nearest to know: hold, tell, anna, fafsa, ben, cookies, safe, notebook,
Nearest to found: lost,
Nearest to found: lost, nike,
Nearest to found: lost, nike, seen,
Nearest to found: lost, nike, seen, floor,
Nearest to found: lost, nike, seen, floor, kepchaja,
Nearest to found: lost, nike, seen, floor, kepchaja, left,
Nearest to found: lost, nike, seen, floor, kepchaja, left, sometime,
Nearest to found: lost, nike, seen, floor, kepchaja, left, sometime, turned,
Nearest to used: various,
Nearest to used: various, statics,
Nearest to used: various, statics, eef,
Nearest to used: various, statics, eef, environment,
Nearest to used: various, statics, eef, environment, finish,
Nearest to used: various, statics, eef, environment, finish, audrey,
Nearest to used: various, statics, eef, environment, finish, audrey, location,
Nearest to used: various, statics, eef, environment, finish, audrey, location, recreation,
Nearest to airport: soccer,
Nearest to airport: soccer, fdaaa,
Nearest to airport: soccer, fdaaa, sep,
Nearest to airport: soccer, fdaaa, sep, monday,
Nearest to airport: soccer, fdaaa, sep, monday, arriving,
Nearest to airport: soccer, fdaaa, sep, monday, arriving, edb,
Nearest to airport: soccer, fdaaa, sep, monday, arriving, edb, driving,
Nearest to airport: soccer, fdaaa, sep, monday, arriving, edb, driving, indy,
Nearest to pm: morning,
Nearest to pm: morning, crosby,
Nearest to pm: morning, crosby, tahoma,
Nearest to pm: morning, crosby, tahoma, category,
Nearest to pm: morning, crosby, tahoma, category, grade,
Nearest to pm: morning, crosby, tahoma, category, grade, arrives,
Nearest to pm: morning, crosby, tahoma, category, grade, arrives, p,
Nearest to pm: morning, crosby, tahoma, category, grade, arrives, p, generic,
Nearest to underline: msonormal,
Nearest to underline: msonormal, serif,
Nearest to underline: msonormal, serif, windowtext,
Nearest to underline: msonormal, serif, windowtext, c,
Nearest to underline: msonormal, serif, windowtext, c, sans,
Nearest to underline: msonormal, serif, windowtext, c, sans, fd,
Nearest to underline: msonormal, serif, windowtext, c, sans, fd, bf,
Nearest to underline: msonormal, serif, windowtext, c, sans, fd, bf, margin,
Nearest to percopo: lakeside,
Nearest to percopo: lakeside, prepare,
Nearest to percopo: lakeside, prepare, deck,
Nearest to percopo: lakeside, prepare, deck, pockets,
Nearest to percopo: lakeside, prepare, deck, pockets, war,
Nearest to percopo: lakeside, prepare, deck, pockets, war, task,
Nearest to percopo: lakeside, prepare, deck, pockets, war, task, west,
Nearest to percopo: lakeside, prepare, deck, pockets, war, task, west, jpg,
Nearest to div: li,
Nearest to div: li, msochpdefault,
Nearest to div: li, msochpdefault, span,
Nearest to div: li, msochpdefault, span, eec,
Nearest to div: li, msochpdefault, span, eec, visited,
Nearest to div: li, msochpdefault, span, eec, visited, bd,
Nearest to div: li, msochpdefault, span, eec, visited, bd, ends,
Nearest to div: li, msochpdefault, span, eec, visited, bd, ends, eb,
Nearest to externalclass: externalclassf,
Nearest to externalclass: externalclassf, externalclasscfbded,
Nearest to externalclass: externalclassf, externalclasscfbded, c,
Nearest to externalclass: externalclassf, externalclasscfbded, c, ebebc,
Nearest to externalclass: externalclassf, externalclasscfbded, c, ebebc, fb,
Nearest to externalclass: externalclassf, externalclasscfbded, c, ebebc, fb, f,
Nearest to externalclass: externalclassf, externalclasscfbded, c, ebebc, fb, f, ce,
Nearest to externalclass: externalclassf, externalclasscfbded, c, ebebc, fb, f, ce, fdaaa,
Nearest to free: clear,
Nearest to free: clear, instead,
Nearest to free: clear, instead, returned,
Nearest to free: clear, instead, returned, bluetooth,
Nearest to free: clear, instead, returned, bluetooth, cbe,
Nearest to free: clear, instead, returned, bluetooth, cbe, resolution,
Nearest to free: clear, instead, returned, bluetooth, cbe, resolution, sashay,
Nearest to free: clear, instead, returned, bluetooth, cbe, resolution, sashay, wellness,
Nearest to margin: sleeping,
Nearest to margin: sleeping, externalclasscfbded,
Nearest to margin: sleeping, externalclasscfbded, top,
Nearest to margin: sleeping, externalclasscfbded, top, drivers,
Nearest to margin: sleeping, externalclasscfbded, top, drivers, dorm,
Nearest to margin: sleeping, externalclasscfbded, top, drivers, dorm, easily,
Nearest to margin: sleeping, externalclasscfbded, top, drivers, dorm, easily, pt,
Nearest to margin: sleeping, externalclasscfbded, top, drivers, dorm, easily, pt, sans,
Average loss at step  62000 :  3.017565117
Average loss at step  64000 :  2.96040086281
Average loss at step  66000 :  2.96264835924
Average loss at step  68000 :  2.98657257581
Average loss at step  70000 :  2.93987221876
Nearest to family: theta,
Nearest to family: theta, latest,
Nearest to family: theta, latest, station,
Nearest to family: theta, latest, station, audrey,
Nearest to family: theta, latest, station, audrey, business,
Nearest to family: theta, latest, station, audrey, business, interaction,
Nearest to family: theta, latest, station, audrey, business, interaction, decoration,
Nearest to family: theta, latest, station, audrey, business, interaction, decoration, inventory,
Nearest to engineering: saddle,
Nearest to engineering: saddle, applied,
Nearest to engineering: saddle, applied, principles,
Nearest to engineering: saddle, applied, principles, graduate,
Nearest to engineering: saddle, applied, principles, graduate, academics,
Nearest to engineering: saddle, applied, principles, graduate, academics, statistics,
Nearest to engineering: saddle, applied, principles, graduate, academics, statistics, management,
Nearest to engineering: saddle, applied, principles, graduate, academics, statistics, management, mark,
Nearest to serif: underline,
Nearest to serif: underline, msonormal,
Nearest to serif: underline, msonormal, windowtext,
Nearest to serif: underline, msonormal, windowtext, f,
Nearest to serif: underline, msonormal, windowtext, f, dbded,
Nearest to serif: underline, msonormal, windowtext, f, dbded, bf,
Nearest to serif: underline, msonormal, windowtext, f, dbded, bf, onto,
Nearest to serif: underline, msonormal, windowtext, f, dbded, bf, onto, fd,
Nearest to help: intramurals,
Nearest to help: intramurals, someone,
Nearest to help: intramurals, someone, power,
Nearest to help: intramurals, someone, power, reading,
Nearest to help: intramurals, someone, power, reading, millerna,
Nearest to help: intramurals, someone, power, reading, millerna, louis,
Nearest to help: intramurals, someone, power, reading, millerna, louis, developers,
Nearest to help: intramurals, someone, power, reading, millerna, louis, developers, rotation,
Nearest to cell: imgur,
Nearest to cell: imgur, solving,
Nearest to cell: imgur, solving, UNK,
Nearest to cell: imgur, solving, UNK, buying,
Nearest to cell: imgur, solving, UNK, buying, fell,
Nearest to cell: imgur, solving, UNK, buying, fell, q,
Nearest to cell: imgur, solving, UNK, buying, fell, q, step,
Nearest to cell: imgur, solving, UNK, buying, fell, q, step, clicking,
Nearest to know: tell,
Nearest to know: tell, hold,
Nearest to know: tell, hold, anna,
Nearest to know: tell, hold, anna, fafsa,
Nearest to know: tell, hold, anna, fafsa, ben,
Nearest to know: tell, hold, anna, fafsa, ben, cookies,
Nearest to know: tell, hold, anna, fafsa, ben, cookies, safe,
Nearest to know: tell, hold, anna, fafsa, ben, cookies, safe, hit,
Nearest to found: lost,
Nearest to found: lost, seen,
Nearest to found: lost, seen, nike,
Nearest to found: lost, seen, nike, kepchaja,
Nearest to found: lost, seen, nike, kepchaja, floor,
Nearest to found: lost, seen, nike, kepchaja, floor, madness,
Nearest to found: lost, seen, nike, kepchaja, floor, madness, turned,
Nearest to found: lost, seen, nike, kepchaja, floor, madness, turned, mistake,
Nearest to used: statics,
Nearest to used: statics, various,
Nearest to used: statics, various, environment,
Nearest to used: statics, various, environment, finish,
Nearest to used: statics, various, environment, finish, eef,
Nearest to used: statics, various, environment, finish, eef, recreation,
Nearest to used: statics, various, environment, finish, eef, recreation, audrey,
Nearest to used: statics, various, environment, finish, eef, recreation, audrey, location,
Nearest to airport: soccer,
Nearest to airport: soccer, fdaaa,
Nearest to airport: soccer, fdaaa, arriving,
Nearest to airport: soccer, fdaaa, arriving, sep,
Nearest to airport: soccer, fdaaa, arriving, sep, monday,
Nearest to airport: soccer, fdaaa, arriving, sep, monday, edb,
Nearest to airport: soccer, fdaaa, arriving, sep, monday, edb, indy,
Nearest to airport: soccer, fdaaa, arriving, sep, monday, edb, indy, adc,
Nearest to pm: morning,
Nearest to pm: morning, tahoma,
Nearest to pm: morning, tahoma, category,
Nearest to pm: morning, tahoma, category, crosby,
Nearest to pm: morning, tahoma, category, crosby, arrives,
Nearest to pm: morning, tahoma, category, crosby, arrives, p,
Nearest to pm: morning, tahoma, category, crosby, arrives, p, grade,
Nearest to pm: morning, tahoma, category, crosby, arrives, p, grade, influence,
Nearest to underline: msonormal,
Nearest to underline: msonormal, serif,
Nearest to underline: msonormal, serif, windowtext,
Nearest to underline: msonormal, serif, windowtext, margin,
Nearest to underline: msonormal, serif, windowtext, margin, sans,
Nearest to underline: msonormal, serif, windowtext, margin, sans, calibri,
Nearest to underline: msonormal, serif, windowtext, margin, sans, calibri, c,
Nearest to underline: msonormal, serif, windowtext, margin, sans, calibri, c, fd,
Nearest to percopo: lakeside,
Nearest to percopo: lakeside, deck,
Nearest to percopo: lakeside, deck, prepare,
Nearest to percopo: lakeside, deck, prepare, war,
Nearest to percopo: lakeside, deck, prepare, war, task,
Nearest to percopo: lakeside, deck, prepare, war, task, pockets,
Nearest to percopo: lakeside, deck, prepare, war, task, pockets, west,
Nearest to percopo: lakeside, deck, prepare, war, task, pockets, west, wearing,
Nearest to div: li,
Nearest to div: li, span,
Nearest to div: li, span, msochpdefault,
Nearest to div: li, span, msochpdefault, b,
Nearest to div: li, span, msochpdefault, b, eec,
Nearest to div: li, span, msochpdefault, b, eec, visited,
Nearest to div: li, span, msochpdefault, b, eec, visited, eb,
Nearest to div: li, span, msochpdefault, b, eec, visited, eb, bd,
Nearest to externalclass: externalclassf,
Nearest to externalclass: externalclassf, externalclasscfbded,
Nearest to externalclass: externalclassf, externalclasscfbded, ebebc,
Nearest to externalclass: externalclassf, externalclasscfbded, ebebc, f,
Nearest to externalclass: externalclassf, externalclasscfbded, ebebc, f, b,
Nearest to externalclass: externalclassf, externalclasscfbded, ebebc, f, b, ddd,
Nearest to externalclass: externalclassf, externalclasscfbded, ebebc, f, b, ddd, aeff,
Nearest to externalclass: externalclassf, externalclasscfbded, ebebc, f, b, ddd, aeff, c,
Nearest to free: clear,
Nearest to free: clear, bluetooth,
Nearest to free: clear, bluetooth, instead,
Nearest to free: clear, bluetooth, instead, cbe,
Nearest to free: clear, bluetooth, instead, cbe, longhj,
Nearest to free: clear, bluetooth, instead, cbe, longhj, resolution,
Nearest to free: clear, bluetooth, instead, cbe, longhj, resolution, wellness,
Nearest to free: clear, bluetooth, instead, cbe, longhj, resolution, wellness, sashay,
Nearest to margin: sleeping,
Nearest to margin: sleeping, top,
Nearest to margin: sleeping, top, externalclasscfbded,
Nearest to margin: sleeping, top, externalclasscfbded, drivers,
Nearest to margin: sleeping, top, externalclasscfbded, drivers, pt,
Nearest to margin: sleeping, top, externalclasscfbded, drivers, pt, dorm,
Nearest to margin: sleeping, top, externalclasscfbded, drivers, pt, dorm, sans,
Nearest to margin: sleeping, top, externalclasscfbded, drivers, pt, dorm, sans, underline,
Average loss at step  72000 :  2.96604223514
Average loss at step  74000 :  2.95119719458
Average loss at step  76000 :  2.91824675316
Average loss at step  78000 :  2.91837686446
Average loss at step  80000 :  2.93021376044
Nearest to family: theta,
Nearest to family: theta, latest,
Nearest to family: theta, latest, station,
Nearest to family: theta, latest, station, audrey,
Nearest to family: theta, latest, station, audrey, decoration,
Nearest to family: theta, latest, station, audrey, decoration, business,
Nearest to family: theta, latest, station, audrey, decoration, business, interaction,
Nearest to family: theta, latest, station, audrey, decoration, business, interaction, inventory,
Nearest to engineering: applied,
Nearest to engineering: applied, saddle,
Nearest to engineering: applied, saddle, graduate,
Nearest to engineering: applied, saddle, graduate, principles,
Nearest to engineering: applied, saddle, graduate, principles, documents,
Nearest to engineering: applied, saddle, graduate, principles, documents, academics,
Nearest to engineering: applied, saddle, graduate, principles, documents, academics, mark,
Nearest to engineering: applied, saddle, graduate, principles, documents, academics, mark, presenting,
Nearest to serif: msonormal,
Nearest to serif: msonormal, underline,
Nearest to serif: msonormal, underline, windowtext,
Nearest to serif: msonormal, underline, windowtext, bf,
Nearest to serif: msonormal, underline, windowtext, bf, f,
Nearest to serif: msonormal, underline, windowtext, bf, f, dbded,
Nearest to serif: msonormal, underline, windowtext, bf, f, dbded, c,
Nearest to serif: msonormal, underline, windowtext, bf, f, dbded, c, onto,
Nearest to help: intramurals,
Nearest to help: intramurals, someone,
Nearest to help: intramurals, someone, reading,
Nearest to help: intramurals, someone, reading, millerna,
Nearest to help: intramurals, someone, reading, millerna, power,
Nearest to help: intramurals, someone, reading, millerna, power, louis,
Nearest to help: intramurals, someone, reading, millerna, power, louis, developers,
Nearest to help: intramurals, someone, reading, millerna, power, louis, developers, dantcm,
Nearest to cell: imgur,
Nearest to cell: imgur, solving,
Nearest to cell: imgur, solving, q,
Nearest to cell: imgur, solving, q, buying,
Nearest to cell: imgur, solving, q, buying, fell,
Nearest to cell: imgur, solving, q, buying, fell, clicking,
Nearest to cell: imgur, solving, q, buying, fell, clicking, claimed,
Nearest to cell: imgur, solving, q, buying, fell, clicking, claimed, rate,
Nearest to know: tell,
Nearest to know: tell, hold,
Nearest to know: tell, hold, anna,
Nearest to know: tell, hold, anna, fafsa,
Nearest to know: tell, hold, anna, fafsa, ben,
Nearest to know: tell, hold, anna, fafsa, ben, yuanz,
Nearest to know: tell, hold, anna, fafsa, ben, yuanz, cookies,
Nearest to know: tell, hold, anna, fafsa, ben, yuanz, cookies, safe,
Nearest to found: lost,
Nearest to found: lost, seen,
Nearest to found: lost, seen, nike,
Nearest to found: lost, seen, nike, madness,
Nearest to found: lost, seen, nike, madness, kepchaja,
Nearest to found: lost, seen, nike, madness, kepchaja, floor,
Nearest to found: lost, seen, nike, madness, kepchaja, floor, sometime,
Nearest to found: lost, seen, nike, madness, kepchaja, floor, sometime, steering,
Nearest to used: statics,
Nearest to used: statics, various,
Nearest to used: statics, various, environment,
Nearest to used: statics, various, environment, practically,
Nearest to used: statics, various, environment, practically, eef,
Nearest to used: statics, various, environment, practically, eef, recreation,
Nearest to used: statics, various, environment, practically, eef, recreation, location,
Nearest to used: statics, various, environment, practically, eef, recreation, location, finish,
Nearest to airport: fdaaa,
Nearest to airport: fdaaa, soccer,
Nearest to airport: fdaaa, soccer, arriving,
Nearest to airport: fdaaa, soccer, arriving, sep,
Nearest to airport: fdaaa, soccer, arriving, sep, edb,
Nearest to airport: fdaaa, soccer, arriving, sep, edb, monday,
Nearest to airport: fdaaa, soccer, arriving, sep, edb, monday, indy,
Nearest to airport: fdaaa, soccer, arriving, sep, edb, monday, indy, driving,
Nearest to pm: morning,
Nearest to pm: morning, crosby,
Nearest to pm: morning, crosby, tahoma,
Nearest to pm: morning, crosby, tahoma, flight,
Nearest to pm: morning, crosby, tahoma, flight, arrives,
Nearest to pm: morning, crosby, tahoma, flight, arrives, grade,
Nearest to pm: morning, crosby, tahoma, flight, arrives, grade, influence,
Nearest to pm: morning, crosby, tahoma, flight, arrives, grade, influence, arriving,
Nearest to underline: msonormal,
Nearest to underline: msonormal, serif,
Nearest to underline: msonormal, serif, windowtext,
Nearest to underline: msonormal, serif, windowtext, sans,
Nearest to underline: msonormal, serif, windowtext, sans, margin,
Nearest to underline: msonormal, serif, windowtext, sans, margin, bf,
Nearest to underline: msonormal, serif, windowtext, sans, margin, bf, b,
Nearest to underline: msonormal, serif, windowtext, sans, margin, bf, b, calibri,
Nearest to percopo: lakeside,
Nearest to percopo: lakeside, war,
Nearest to percopo: lakeside, war, prepare,
Nearest to percopo: lakeside, war, prepare, deck,
Nearest to percopo: lakeside, war, prepare, deck, west,
Nearest to percopo: lakeside, war, prepare, deck, west, task,
Nearest to percopo: lakeside, war, prepare, deck, west, task, wearing,
Nearest to percopo: lakeside, war, prepare, deck, west, task, wearing, phone,
Nearest to div: li,
Nearest to div: li, span,
Nearest to div: li, span, msochpdefault,
Nearest to div: li, span, msochpdefault, eec,
Nearest to div: li, span, msochpdefault, eec, b,
Nearest to div: li, span, msochpdefault, eec, b, visited,
Nearest to div: li, span, msochpdefault, eec, b, visited, eb,
Nearest to div: li, span, msochpdefault, eec, b, visited, eb, bd,
Nearest to externalclass: externalclassf,
Nearest to externalclass: externalclassf, externalclasscfbded,
Nearest to externalclass: externalclassf, externalclasscfbded, b,
Nearest to externalclass: externalclassf, externalclasscfbded, b, f,
Nearest to externalclass: externalclassf, externalclasscfbded, b, f, ebebc,
Nearest to externalclass: externalclassf, externalclasscfbded, b, f, ebebc, externalclassdf,
Nearest to externalclass: externalclassf, externalclasscfbded, b, f, ebebc, externalclassdf, fb,
Nearest to externalclass: externalclassf, externalclasscfbded, b, f, ebebc, externalclassdf, fb, fbc,
Nearest to free: clear,
Nearest to free: clear, bluetooth,
Nearest to free: clear, bluetooth, instead,
Nearest to free: clear, bluetooth, instead, sashay,
Nearest to free: clear, bluetooth, instead, sashay, cbe,
Nearest to free: clear, bluetooth, instead, sashay, cbe, longhj,
Nearest to free: clear, bluetooth, instead, sashay, cbe, longhj, resolution,
Nearest to free: clear, bluetooth, instead, sashay, cbe, longhj, resolution, wellness,
Nearest to margin: sleeping,
Nearest to margin: sleeping, externalclasscfbded,
Nearest to margin: sleeping, externalclasscfbded, top,
Nearest to margin: sleeping, externalclasscfbded, top, msonormal,
Nearest to margin: sleeping, externalclasscfbded, top, msonormal, pt,
Nearest to margin: sleeping, externalclasscfbded, top, msonormal, pt, drivers,
Nearest to margin: sleeping, externalclasscfbded, top, msonormal, pt, drivers, underline,
Nearest to margin: sleeping, externalclasscfbded, top, msonormal, pt, drivers, underline, sans,
Average loss at step  82000 :  2.92459851122
Average loss at step  84000 :  2.90630262828
Average loss at step  86000 :  2.93822360212
Average loss at step  88000 :  2.90336518288
Average loss at step  90000 :  2.87907069296
Nearest to family: theta,
Nearest to family: theta, station,
Nearest to family: theta, station, audrey,
Nearest to family: theta, station, audrey, latest,
Nearest to family: theta, station, audrey, latest, decoration,
Nearest to family: theta, station, audrey, latest, decoration, inventory,
Nearest to family: theta, station, audrey, latest, decoration, inventory, interaction,
Nearest to family: theta, station, audrey, latest, decoration, inventory, interaction, business,
Nearest to engineering: applied,
Nearest to engineering: applied, saddle,
Nearest to engineering: applied, saddle, graduate,
Nearest to engineering: applied, saddle, graduate, principles,
Nearest to engineering: applied, saddle, graduate, principles, documents,
Nearest to engineering: applied, saddle, graduate, principles, documents, academics,
Nearest to engineering: applied, saddle, graduate, principles, documents, academics, statistics,
Nearest to engineering: applied, saddle, graduate, principles, documents, academics, statistics, materials,
Nearest to serif: msonormal,
Nearest to serif: msonormal, underline,
Nearest to serif: msonormal, underline, windowtext,
Nearest to serif: msonormal, underline, windowtext, f,
Nearest to serif: msonormal, underline, windowtext, f, bf,
Nearest to serif: msonormal, underline, windowtext, f, bf, dbded,
Nearest to serif: msonormal, underline, windowtext, f, bf, dbded, b,
Nearest to serif: msonormal, underline, windowtext, f, bf, dbded, b, onto,
Nearest to help: intramurals,
Nearest to help: intramurals, someone,
Nearest to help: intramurals, someone, millerna,
Nearest to help: intramurals, someone, millerna, power,
Nearest to help: intramurals, someone, millerna, power, dantcm,
Nearest to help: intramurals, someone, millerna, power, dantcm, reading,
Nearest to help: intramurals, someone, millerna, power, dantcm, reading, developers,
Nearest to help: intramurals, someone, millerna, power, dantcm, reading, developers, louis,
Nearest to cell: imgur,
Nearest to cell: imgur, solving,
Nearest to cell: imgur, solving, UNK,
Nearest to cell: imgur, solving, UNK, q,
Nearest to cell: imgur, solving, UNK, q, buying,
Nearest to cell: imgur, solving, UNK, q, buying, fell,
Nearest to cell: imgur, solving, UNK, q, buying, fell, clicking,
Nearest to cell: imgur, solving, UNK, q, buying, fell, clicking, rate,
Nearest to know: tell,
Nearest to know: tell, anna,
Nearest to know: tell, anna, hold,
Nearest to know: tell, anna, hold, fafsa,
Nearest to know: tell, anna, hold, fafsa, ben,
Nearest to know: tell, anna, hold, fafsa, ben, yuanz,
Nearest to know: tell, anna, hold, fafsa, ben, yuanz, circular,
Nearest to know: tell, anna, hold, fafsa, ben, yuanz, circular, hit,
Nearest to found: lost,
Nearest to found: lost, seen,
Nearest to found: lost, seen, nike,
Nearest to found: lost, seen, nike, madness,
Nearest to found: lost, seen, nike, madness, kepchaja,
Nearest to found: lost, seen, nike, madness, kepchaja, bracelet,
Nearest to found: lost, seen, nike, madness, kepchaja, bracelet, mistake,
Nearest to found: lost, seen, nike, madness, kepchaja, bracelet, mistake, steering,
Nearest to used: statics,
Nearest to used: statics, environment,
Nearest to used: statics, environment, various,
Nearest to used: statics, environment, various, practically,
Nearest to used: statics, environment, various, practically, finish,
Nearest to used: statics, environment, various, practically, finish, eef,
Nearest to used: statics, environment, various, practically, finish, eef, excited,
Nearest to used: statics, environment, various, practically, finish, eef, excited, location,
Nearest to airport: fdaaa,
Nearest to airport: fdaaa, arriving,
Nearest to airport: fdaaa, arriving, sep,
Nearest to airport: fdaaa, arriving, sep, edb,
Nearest to airport: fdaaa, arriving, sep, edb, soccer,
Nearest to airport: fdaaa, arriving, sep, edb, soccer, monday,
Nearest to airport: fdaaa, arriving, sep, edb, soccer, monday, indy,
Nearest to airport: fdaaa, arriving, sep, edb, soccer, monday, indy, mass,
Nearest to pm: morning,
Nearest to pm: morning, p,
Nearest to pm: morning, p, crosby,
Nearest to pm: morning, p, crosby, influence,
Nearest to pm: morning, p, crosby, influence, flight,
Nearest to pm: morning, p, crosby, influence, flight, grade,
Nearest to pm: morning, p, crosby, influence, flight, grade, tahoma,
Nearest to pm: morning, p, crosby, influence, flight, grade, tahoma, arrives,
Nearest to underline: msonormal,
Nearest to underline: msonormal, serif,
Nearest to underline: msonormal, serif, windowtext,
Nearest to underline: msonormal, serif, windowtext, margin,
Nearest to underline: msonormal, serif, windowtext, margin, sans,
Nearest to underline: msonormal, serif, windowtext, margin, sans, b,
Nearest to underline: msonormal, serif, windowtext, margin, sans, b, posted,
Nearest to underline: msonormal, serif, windowtext, margin, sans, b, posted, calibri,
Nearest to percopo: lakeside,
Nearest to percopo: lakeside, war,
Nearest to percopo: lakeside, war, prepare,
Nearest to percopo: lakeside, war, prepare, west,
Nearest to percopo: lakeside, war, prepare, west, deck,
Nearest to percopo: lakeside, war, prepare, west, deck, triplets,
Nearest to percopo: lakeside, war, prepare, west, deck, triplets, task,
Nearest to percopo: lakeside, war, prepare, west, deck, triplets, task, wearing,
Nearest to div: li,
Nearest to div: li, span,
Nearest to div: li, span, msochpdefault,
Nearest to div: li, span, msochpdefault, b,
Nearest to div: li, span, msochpdefault, b, eec,
Nearest to div: li, span, msochpdefault, b, eec, visited,
Nearest to div: li, span, msochpdefault, b, eec, visited, eb,
Nearest to div: li, span, msochpdefault, b, eec, visited, eb, externalclass,
Nearest to externalclass: externalclassf,
Nearest to externalclass: externalclassf, externalclasscfbded,
Nearest to externalclass: externalclassf, externalclasscfbded, b,
Nearest to externalclass: externalclassf, externalclasscfbded, b, ebebc,
Nearest to externalclass: externalclassf, externalclasscfbded, b, ebebc, fbc,
Nearest to externalclass: externalclassf, externalclasscfbded, b, ebebc, fbc, fdaaa,
Nearest to externalclass: externalclassf, externalclasscfbded, b, ebebc, fbc, fdaaa, fb,
Nearest to externalclass: externalclassf, externalclasscfbded, b, ebebc, fbc, fdaaa, fb, externalclassdf,
Nearest to free: clear,
Nearest to free: clear, bluetooth,
Nearest to free: clear, bluetooth, sashay,
Nearest to free: clear, bluetooth, sashay, cbe,
Nearest to free: clear, bluetooth, sashay, cbe, longhj,
Nearest to free: clear, bluetooth, sashay, cbe, longhj, instead,
Nearest to free: clear, bluetooth, sashay, cbe, longhj, instead, wellness,
Nearest to free: clear, bluetooth, sashay, cbe, longhj, instead, wellness, returned,
Nearest to margin: sleeping,
Nearest to margin: sleeping, top,
Nearest to margin: sleeping, top, externalclasscfbded,
Nearest to margin: sleeping, top, externalclasscfbded, drivers,
Nearest to margin: sleeping, top, externalclasscfbded, drivers, msonormal,
Nearest to margin: sleeping, top, externalclasscfbded, drivers, msonormal, sans,
Nearest to margin: sleeping, top, externalclasscfbded, drivers, msonormal, sans, font,
Nearest to margin: sleeping, top, externalclasscfbded, drivers, msonormal, sans, font, underline,
Average loss at step  92000 :  2.90463174236
Average loss at step  94000 :  2.89727564466
Average loss at step  96000 :  2.86044349223
Average loss at step  98000 :  2.90248500293
Average loss at step  100000 :  2.91740509504
Nearest to family: theta,
Nearest to family: theta, decoration,
Nearest to family: theta, decoration, audrey,
Nearest to family: theta, decoration, audrey, latest,
Nearest to family: theta, decoration, audrey, latest, station,
Nearest to family: theta, decoration, audrey, latest, station, inventory,
Nearest to family: theta, decoration, audrey, latest, station, inventory, interaction,
Nearest to family: theta, decoration, audrey, latest, station, inventory, interaction, kroger,
Nearest to engineering: applied,
Nearest to engineering: applied, saddle,
Nearest to engineering: applied, saddle, graduate,
Nearest to engineering: applied, saddle, graduate, documents,
Nearest to engineering: applied, saddle, graduate, documents, statistics,
Nearest to engineering: applied, saddle, graduate, documents, statistics, principles,
Nearest to engineering: applied, saddle, graduate, documents, statistics, principles, dynamics,
Nearest to engineering: applied, saddle, graduate, documents, statistics, principles, dynamics, academics,
Nearest to serif: msonormal,
Nearest to serif: msonormal, underline,
Nearest to serif: msonormal, underline, c,
Nearest to serif: msonormal, underline, c, windowtext,
Nearest to serif: msonormal, underline, c, windowtext, b,
Nearest to serif: msonormal, underline, c, windowtext, b, bf,
Nearest to serif: msonormal, underline, c, windowtext, b, bf, f,
Nearest to serif: msonormal, underline, c, windowtext, b, bf, f, fd,
Nearest to help: intramurals,
Nearest to help: intramurals, someone,
Nearest to help: intramurals, someone, millerna,
Nearest to help: intramurals, someone, millerna, developers,
Nearest to help: intramurals, someone, millerna, developers, UNK,
Nearest to help: intramurals, someone, millerna, developers, UNK, dantcm,
Nearest to help: intramurals, someone, millerna, developers, UNK, dantcm, reading,
Nearest to help: intramurals, someone, millerna, developers, UNK, dantcm, reading, component,
Nearest to cell: imgur,
Nearest to cell: imgur, q,
Nearest to cell: imgur, q, solving,
Nearest to cell: imgur, q, solving, buying,
Nearest to cell: imgur, q, solving, buying, rate,
Nearest to cell: imgur, q, solving, buying, rate, clicking,
Nearest to cell: imgur, q, solving, buying, rate, clicking, fell,
Nearest to cell: imgur, q, solving, buying, rate, clicking, fell, msochpdefault,
Nearest to know: tell,
Nearest to know: tell, ben,
Nearest to know: tell, ben, fafsa,
Nearest to know: tell, ben, fafsa, anna,
Nearest to know: tell, ben, fafsa, anna, hold,
Nearest to know: tell, ben, fafsa, anna, hold, say,
Nearest to know: tell, ben, fafsa, anna, hold, say, yuanz,
Nearest to know: tell, ben, fafsa, anna, hold, say, yuanz, notebook,
Nearest to found: lost,
Nearest to found: lost, seen,
Nearest to found: lost, seen, nike,
Nearest to found: lost, seen, nike, madness,
Nearest to found: lost, seen, nike, madness, kepchaja,
Nearest to found: lost, seen, nike, madness, kepchaja, mistake,
Nearest to found: lost, seen, nike, madness, kepchaja, mistake, baa,
Nearest to found: lost, seen, nike, madness, kepchaja, mistake, baa, bracelet,
Nearest to used: environment,
Nearest to used: environment, various,
Nearest to used: environment, various, statics,
Nearest to used: environment, various, statics, location,
Nearest to used: environment, various, statics, location, finish,
Nearest to used: environment, various, statics, location, finish, practically,
Nearest to used: environment, various, statics, location, finish, practically, laundry,
Nearest to used: environment, various, statics, location, finish, practically, laundry, recreation,
Nearest to airport: arriving,
Nearest to airport: arriving, sep,
Nearest to airport: arriving, sep, fdaaa,
Nearest to airport: arriving, sep, fdaaa, indy,
Nearest to airport: arriving, sep, fdaaa, indy, edb,
Nearest to airport: arriving, sep, fdaaa, indy, edb, monday,
Nearest to airport: arriving, sep, fdaaa, indy, edb, monday, soccer,
Nearest to airport: arriving, sep, fdaaa, indy, edb, monday, soccer, mass,
Nearest to pm: morning,
Nearest to pm: morning, influence,
Nearest to pm: morning, influence, crosby,
Nearest to pm: morning, influence, crosby, p,
Nearest to pm: morning, influence, crosby, p, grade,
Nearest to pm: morning, influence, crosby, p, grade, tahoma,
Nearest to pm: morning, influence, crosby, p, grade, tahoma, flight,
Nearest to pm: morning, influence, crosby, p, grade, tahoma, flight, kahn,
Nearest to underline: msonormal,
Nearest to underline: msonormal, serif,
Nearest to underline: msonormal, serif, windowtext,
Nearest to underline: msonormal, serif, windowtext, c,
Nearest to underline: msonormal, serif, windowtext, c, b,
Nearest to underline: msonormal, serif, windowtext, c, b, fd,
Nearest to underline: msonormal, serif, windowtext, c, b, fd, margin,
Nearest to underline: msonormal, serif, windowtext, c, b, fd, margin, sans,
Nearest to percopo: lakeside,
Nearest to percopo: lakeside, war,
Nearest to percopo: lakeside, war, prepare,
Nearest to percopo: lakeside, war, prepare, gun,
Nearest to percopo: lakeside, war, prepare, gun, triplets,
Nearest to percopo: lakeside, war, prepare, gun, triplets, task,
Nearest to percopo: lakeside, war, prepare, gun, triplets, task, west,
Nearest to percopo: lakeside, war, prepare, gun, triplets, task, west, deck,
Nearest to div: li,
Nearest to div: li, span,
Nearest to div: li, span, msochpdefault,
Nearest to div: li, span, msochpdefault, b,
Nearest to div: li, span, msochpdefault, b, visited,
Nearest to div: li, span, msochpdefault, b, visited, eec,
Nearest to div: li, span, msochpdefault, b, visited, eec, f,
Nearest to div: li, span, msochpdefault, b, visited, eec, f, eb,
Nearest to externalclass: externalclasscfbded,
Nearest to externalclass: externalclasscfbded, externalclassf,
Nearest to externalclass: externalclasscfbded, externalclassf, b,
Nearest to externalclass: externalclasscfbded, externalclassf, b, c,
Nearest to externalclass: externalclasscfbded, externalclassf, b, c, ebebc,
Nearest to externalclass: externalclasscfbded, externalclassf, b, c, ebebc, externalclassdf,
Nearest to externalclass: externalclasscfbded, externalclassf, b, c, ebebc, externalclassdf, fdaaa,
Nearest to externalclass: externalclasscfbded, externalclassf, b, c, ebebc, externalclassdf, fdaaa, dad,
Nearest to free: clear,
Nearest to free: clear, bluetooth,
Nearest to free: clear, bluetooth, sashay,
Nearest to free: clear, bluetooth, sashay, cbe,
Nearest to free: clear, bluetooth, sashay, cbe, instead,
Nearest to free: clear, bluetooth, sashay, cbe, instead, chris,
Nearest to free: clear, bluetooth, sashay, cbe, instead, chris, longhj,
Nearest to free: clear, bluetooth, sashay, cbe, instead, chris, longhj, jpeg,
Nearest to margin: sleeping,
Nearest to margin: sleeping, externalclasscfbded,
Nearest to margin: sleeping, externalclasscfbded, top,
Nearest to margin: sleeping, externalclasscfbded, top, drivers,
Nearest to margin: sleeping, externalclasscfbded, top, drivers, pt,
Nearest to margin: sleeping, externalclasscfbded, top, drivers, pt, sans,
Nearest to margin: sleeping, externalclasscfbded, top, drivers, pt, sans, msonormal,
Nearest to margin: sleeping, externalclasscfbded, top, drivers, pt, sans, msonormal, font,

In [35]:
from sklearn.manifold import TSNE
import matplotlib

import matplotlib.pyplot as plt
%pylab inline 
# Step 6: Visualize the embeddings.
def plot_with_labels(low_dim_embs, labels, filename='test.png'):
    assert low_dim_embs.shape[0] >= len(labels), "More labels than embeddings"
    plt.figure(figsize=(18, 18))  #in inches
    for i, label in enumerate(labels):
        x, y = low_dim_embs[i,:]
        plt.scatter(x, y)
        plt.annotate(label,
                 xy=(x, y),
                 xytext=(5, 2),
                 textcoords='offset points',
                 ha='right',
                 va='bottom')

    plt.savefig(filename)


Populating the interactive namespace from numpy and matplotlib
WARNING: pylab import has clobbered these variables: ['step', 'random', 'norm']
`%matplotlib` prevents importing * from pylab and numpy

In [36]:
tsne = TSNE(perplexity=30, n_components=2, init='pca', n_iter=5000)
plot_only = 500
low_dim_embs = tsne.fit_transform(final_embeddings[:plot_only,:])
labels = [reverse_dictionary[i] for i in xrange(plot_only)]
    

len(labels)
low_dim_embs.shape


Out[36]:
(500, 2)

In [37]:
def findembeding(word):
    if word in dictionary:
        value = dictionary[word]
        #print('in dict:%d',value)
        return final_embeddings[value]
    else:
        #print('not in dict')
        return final_embeddings[0]

In [38]:
#represent an email with a 128 dimension vector
def meanonemail(i):
    onelist = []
    result = np.ones(128)
    result = np.append([result], [result], axis=0)
    array = sentence_to_words(titles[i][0])
    onelist.extend(array)
    if(isinstance(body[i][0], str)):
        array = sentence_to_words(body[i][0])
        onelist.extend(array)
    N = len(onelist)
    
    # print(onelist)
   
    for count in range(N):
        word = onelist[count]
        embed = findembeding(word)
        
        result = np.append(result, [embed], axis=0)
    
    row = result.shape[0]
    result = result[2:row]
    
    return np.mean(result, axis=0)

In [41]:
result1 = meanonemail(0)
result1.shape


Out[41]:
(128,)

In [43]:
#this result should be saved
def representeveryemail():
    result = []
    for i in range(N):
        #print(i)
        result.append(meanonemail(i))
    return result

In [44]:
result = representeveryemail()

In [45]:
import csv

In [46]:
with open('email.csv', 'w') as mycsvfile:
    thedatawriter = csv.writer(mycsvfile)
    for row in result:
        thedatawriter.writerow(row)

In [47]:
def findnearest(index):
    distancelist = []
    if(index == 0):
        for i in range(N-1):
            #print(i+1)
            dis = numpy.linalg.norm(meanonemail(0)-meanonemail(i+1)) 
            distancelist.append(dis)
        
    else:
        for i in range(index):
            #print(i)
            dis = numpy.linalg.norm(meanonemail(index)-meanonemail(i)) 
            distancelist.append(dis)
        for i in range(N-index-1):
            #print(i+index+1)
            dis = numpy.linalg.norm(meanonemail(index)-meanonemail(i+index+1)) 
            distancelist.append(dis)
    ind = np.argmin(distancelist)
    print('original email')
    print(body[index][0])
    print('nearest email found')
    print(body[ind][0])
    #return distancelist

In [48]:
findnearest(700)


original email
Selling SAW video game for the PS3, I have gotten all of the enjoyment i can out of this game and have not picked it up in a while.  The game still works and I'm asking for about 20$ rather not go any lower than that but will entertain offers.
nearest email found
I'm looking for someone to practice playing tennis with during the weekends over the summer. All levels are welcome! If interested, please contact me at caijy@rose-hulman.edu or 6462097956

In [ ]: