

In [1]:

    
import keras









    



Using TensorFlow backend.

原始資料來源的 SQL，這是抽樣過的資料，當中也有一筆資料是修改過的，因為當天 Server 似乎出了一些問題，導至流量大幅下降



In [2]:

    
sql = """
SELECT 
date,count(distinct cookie_pta) as uv
from
TABLE_DATE_RANGE(pixinsight.article_visitor_log_1_100_, TIMESTAMP('2017-01-01'), CURRENT_TIMESTAMP())
where venue = 'pixnet'
group by date
order by date
"""



In [3]:

    
from os import environ
# load and plot dataset
import pandas as pd
from pandas import read_csv
from pandas import datetime
from matplotlib import pyplot
import matplotlib.dates as mdates

%matplotlib notebook

# %matplotlib inline  

# load dataset
def parser(x):
    return datetime.strptime(x, '%Y%m%d')

series = pd.read_gbq(sql,project_id=environ['PROJECT_ID'], verbose=False, private_key=environ['GOOGLE_KEY'])#,header=0, parse_dates=[0], index_col='date', squeeze=True, date_parser=parser)
series['date'] = pd.to_datetime(series['date'],format='%Y%m%d')
series.index = series['date']
del series['date']

# summarize first few rows
print(series.head())









    



               uv
date             
2017-01-01  38633
2017-01-02  39509
2017-01-03  42734
2017-01-04  43611
2017-01-05  40036

進行 scale to 0-1 ，方便作為 input 及 output (因為 sigmoid 介於 0~1 之間)



In [4]:

    
from sklearn.preprocessing import scale,MinMaxScaler
scaler = MinMaxScaler()



In [5]:

    
x = series.values



In [6]:

    
x = x.reshape([x.shape[0],1])



In [7]:

    
scaler.fit(x)









    



/usr/local/lib/python3.5/dist-packages/sklearn/utils/validation.py:475: DataConversionWarning: Data with input dtype int64 was converted to float64 by MinMaxScaler.
  warnings.warn(msg, DataConversionWarning)






    Out[7]:





MinMaxScaler(copy=True, feature_range=(0, 1))



In [8]:

    
x_scaled = scaler.transform(x)



In [9]:

    
pyplot.figure()
pyplot.plot(x_scaled)
pyplot.show()

產生 x,y pair

舉列來說假設將 Step Size 設為 4 天，故一筆 Training Data ，為連續 4 天的流量。再來利用這４天的資料來預測第 5 天的流量
綠色的部是 Training Data(前4天的資料)，藍色的部份是需要被預測的部份。示意如下圖



In [10]:

    
#往回看 30 天前的每一筆資料
step_size = 15



In [11]:

    
print("原始資料長度:{}".format(x_scaled.shape))









    



原始資料長度:(312, 1)



In [12]:

    
def window_stack(a, stepsize=1, width=3):
    return np.hstack( a[i:1+i-width or None:stepsize] for i in range(0,width) )

import numpy as np
train_x = window_stack(x_scaled, stepsize=1, width=step_size)



In [13]:

    
# 最後一筆資料要放棄，因為沒有未來的答案作驗證

train_x = train_x[:-1]
train_x.shape









    Out[13]:





(297, 15)



In [14]:

    
# 請注意千萬不將每一筆(Row) 當中的最後一天資料作為 Training Data 中的 Input Data
train_y = np.array([i for i in x_scaled[step_size:]])

確認產出來的 Training Data 沒有包含到 Testing Data



In [15]:

    
train_y.shape









    Out[15]:





(297, 1)



In [16]:

    
train_x[0]









    Out[16]:





array([ 0.80070082,  0.82187047,  0.89980667,  0.92100048,  0.83460609,
        0.91906718,  0.88105365,  0.93615273,  0.89059932,  0.87539874,
        0.88653939,  0.88124698,  0.81500725,  0.82450459,  0.84775254])



In [17]:

    
train_x[1]









    Out[17]:





array([ 0.82187047,  0.89980667,  0.92100048,  0.83460609,  0.91906718,
        0.88105365,  0.93615273,  0.89059932,  0.87539874,  0.88653939,
        0.88124698,  0.81500725,  0.82450459,  0.84775254,  0.87426293])



In [18]:

    
train_y[0]









    Out[18]:





array([ 0.87426293])

Design Graph



In [19]:

    
# reshape input to be [samples, time steps, features]
trainX = np.reshape(train_x, (train_x.shape[0], step_size, 1))



In [20]:

    
from keras import Sequential
from keras.layers import LSTM,Dense
# create and fit the LSTM network
model = Sequential()
# input_shape(step_size,feature_dim)
model.add(LSTM(4, input_shape=(step_size,1), unroll=True))
model.add(Dense(1))
model.compile(loss='mean_squared_error', optimizer='adam',metrics=['accuracy'])
model.summary()









    



_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
lstm_1 (LSTM)                (None, 4)                 96        
_________________________________________________________________
dense_1 (Dense)              (None, 1)                 5         
=================================================================
Total params: 101
Trainable params: 101
Non-trainable params: 0
_________________________________________________________________

最後30 筆資料不要看



In [21]:

    
validation_size = 60



In [52]:

    
val_loss = []
loss = []
for _ in range(400):
    history = model.fit(trainX[:-1*validation_size],
              train_y[:-1*validation_size],
              epochs=1,shuffle=False, 
              validation_data=(trainX[-1*validation_size:],
              train_y[-1*validation_size:]))
    
    loss.append(history.history['loss'])
    val_loss.append(history.history['val_loss'])
    model.reset_states()









    



Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 669us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 668us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 663us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 660us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 633us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 626us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 636us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 634us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 688us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 768us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 745us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 653us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 761us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 693us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 656us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 662us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 724us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 689us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 660us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 671us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 636us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 660us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 655us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 631us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 632us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 635us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 691us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 669us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 668us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 633us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 676us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 668us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 681us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 656us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 797us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 821us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 666us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 701us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 661us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 631us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 634us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 636us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 633us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 628us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 658us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 656us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 653us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 653us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 658us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 670us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 656us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 636us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 669us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 662us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 636us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 673us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 653us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 651us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 677us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 653us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 662us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 637us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 655us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 656us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 651us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 653us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 666us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 637us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 657us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 660us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 636us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 651us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 637us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 653us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 658us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 635us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 637us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 640us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 661us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 633us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 634us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 640us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 640us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 662us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 668us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 640us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 669us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 660us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 651us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 701us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 671us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 662us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 658us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 663us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 679us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 679us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 665us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 630us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 666us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 636us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 628us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 635us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 636us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 636us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 661us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 655us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 633us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 634us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 655us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 658us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 637us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 640us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 651us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 655us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 662us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 635us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 656us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 651us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 659us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 672us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 670us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 659us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 670us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 658us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 655us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 651us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 658us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 637us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 651us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 637us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 640us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 655us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 661us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 665us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 633us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 651us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 649us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 670us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 665us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 658us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 672us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 653us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 635us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 655us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 659us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 637us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 636us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 631us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 651us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 657us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 651us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 640us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 660us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 629us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 625us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 659us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 666us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 668us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 650us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 639us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 637us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 646us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 640us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 640us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 645us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 653us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 631us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 633us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 638us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 652us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 630us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 657us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 642us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 647us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 630us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 641us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 643us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 654us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 640us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 644us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 657us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00
Train on 237 samples, validate on 60 samples
Epoch 1/1
237/237 [==============================] - 0s 648us/step - loss: 0.0061 - acc: 0.0042 - val_loss: 0.0012 - val_acc: 0.0000e+00

看一下 Error Rate 曲線



In [53]:

    
pyplot.figure()
pyplot.plot(loss)
pyplot.plot(val_loss)
pyplot.show()

看一下曲線擬合效果



In [54]:

    
predict_y = model.predict(trainX)



In [55]:

    
train_y.shape









    Out[55]:





(297, 1)



In [56]:

    
pyplot.figure()
pyplot.plot(scaler.inverse_transform(predict_y))
pyplot.plot(scaler.inverse_transform(train_y))

pyplot.show()

來預測最後 60 天資料預出來的結果



In [57]:

    
predict_y = model.predict(trainX[-1*validation_size:])



In [58]:

    
predict_y = scaler.inverse_transform(predict_y)



In [59]:

    
predict_y.shape









    Out[59]:





(60, 1)



In [60]:

    
pyplot.figure()
pyplot.plot(x[-1*(validation_size+1):-1])
pyplot.plot(predict_y)


pyplot.show()

心得觀察

LSTM 可以學習到 Period Pattern 是沒有問題的，但是似乎對於大幅的震盪以目前的 Model 來說無法完全的 Catch 到，但是還是有學到漲幅的趨勢預測
至於 LSTM 要如何調整震盪的幅度有兩個想法可以實驗看看
- 直接 Modified Training，將震盪幅度加大
- 修改 Loss Function ，把平方改為 2.x 次方不知道是否有效果



In [ ]: