Use the pseudocode you came up with in class to write your own 5-fold cross-validation function that splits the data set into

  • Don't forget to shuffle the input before assigning to the splits

  • You can use the fit

  • Test the results with the sklearn cross_val_score
  • In your PR, discuss what challenges you had creating this function and if it helped you better understand cross validation

define the cross_validation function(model, target, attributes):

-take the length of attributes array

-divide length of attribute array by 5

-shuffle the data based on the index

-split attribute array into five subsets

-for each subset of the attribute array:

*assign four portions of that subset to training
*fit model to training 
*assign one portion of that subset to test
*predict on test data
*score model = compare predicted y to actual y

In [92]:
import pandas as pd
%matplotlib inline
from sklearn import datasets
from sklearn import tree
from sklearn import metrics
import matplotlib.pyplot as plt
from random import shuffle
import numpy as np

In [93]:
iris = datasets.load_iris()

In [94]:
iris


Out[94]:
{'DESCR': 'Iris Plants Database\n\nNotes\n-----\nData Set Characteristics:\n    :Number of Instances: 150 (50 in each of three classes)\n    :Number of Attributes: 4 numeric, predictive attributes and the class\n    :Attribute Information:\n        - sepal length in cm\n        - sepal width in cm\n        - petal length in cm\n        - petal width in cm\n        - class:\n                - Iris-Setosa\n                - Iris-Versicolour\n                - Iris-Virginica\n    :Summary Statistics:\n\n    ============== ==== ==== ======= ===== ====================\n                    Min  Max   Mean    SD   Class Correlation\n    ============== ==== ==== ======= ===== ====================\n    sepal length:   4.3  7.9   5.84   0.83    0.7826\n    sepal width:    2.0  4.4   3.05   0.43   -0.4194\n    petal length:   1.0  6.9   3.76   1.76    0.9490  (high!)\n    petal width:    0.1  2.5   1.20  0.76     0.9565  (high!)\n    ============== ==== ==== ======= ===== ====================\n\n    :Missing Attribute Values: None\n    :Class Distribution: 33.3% for each of 3 classes.\n    :Creator: R.A. Fisher\n    :Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)\n    :Date: July, 1988\n\nThis is a copy of UCI ML iris datasets.\nhttp://archive.ics.uci.edu/ml/datasets/Iris\n\nThe famous Iris database, first used by Sir R.A Fisher\n\nThis is perhaps the best known database to be found in the\npattern recognition literature.  Fisher\'s paper is a classic in the field and\nis referenced frequently to this day.  (See Duda & Hart, for example.)  The\ndata set contains 3 classes of 50 instances each, where each class refers to a\ntype of iris plant.  One class is linearly separable from the other 2; the\nlatter are NOT linearly separable from each other.\n\nReferences\n----------\n   - Fisher,R.A. "The use of multiple measurements in taxonomic problems"\n     Annual Eugenics, 7, Part II, 179-188 (1936); also in "Contributions to\n     Mathematical Statistics" (John Wiley, NY, 1950).\n   - Duda,R.O., & Hart,P.E. (1973) Pattern Classification and Scene Analysis.\n     (Q327.D83) John Wiley & Sons.  ISBN 0-471-22361-1.  See page 218.\n   - Dasarathy, B.V. (1980) "Nosing Around the Neighborhood: A New System\n     Structure and Classification Rule for Recognition in Partially Exposed\n     Environments".  IEEE Transactions on Pattern Analysis and Machine\n     Intelligence, Vol. PAMI-2, No. 1, 67-71.\n   - Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule".  IEEE Transactions\n     on Information Theory, May 1972, 431-433.\n   - See also: 1988 MLC Proceedings, 54-64.  Cheeseman et al"s AUTOCLASS II\n     conceptual clustering system finds 3 classes in the data.\n   - Many, many more ...\n',
 'data': array([[ 5.1,  3.5,  1.4,  0.2],
        [ 4.9,  3. ,  1.4,  0.2],
        [ 4.7,  3.2,  1.3,  0.2],
        [ 4.6,  3.1,  1.5,  0.2],
        [ 5. ,  3.6,  1.4,  0.2],
        [ 5.4,  3.9,  1.7,  0.4],
        [ 4.6,  3.4,  1.4,  0.3],
        [ 5. ,  3.4,  1.5,  0.2],
        [ 4.4,  2.9,  1.4,  0.2],
        [ 4.9,  3.1,  1.5,  0.1],
        [ 5.4,  3.7,  1.5,  0.2],
        [ 4.8,  3.4,  1.6,  0.2],
        [ 4.8,  3. ,  1.4,  0.1],
        [ 4.3,  3. ,  1.1,  0.1],
        [ 5.8,  4. ,  1.2,  0.2],
        [ 5.7,  4.4,  1.5,  0.4],
        [ 5.4,  3.9,  1.3,  0.4],
        [ 5.1,  3.5,  1.4,  0.3],
        [ 5.7,  3.8,  1.7,  0.3],
        [ 5.1,  3.8,  1.5,  0.3],
        [ 5.4,  3.4,  1.7,  0.2],
        [ 5.1,  3.7,  1.5,  0.4],
        [ 4.6,  3.6,  1. ,  0.2],
        [ 5.1,  3.3,  1.7,  0.5],
        [ 4.8,  3.4,  1.9,  0.2],
        [ 5. ,  3. ,  1.6,  0.2],
        [ 5. ,  3.4,  1.6,  0.4],
        [ 5.2,  3.5,  1.5,  0.2],
        [ 5.2,  3.4,  1.4,  0.2],
        [ 4.7,  3.2,  1.6,  0.2],
        [ 4.8,  3.1,  1.6,  0.2],
        [ 5.4,  3.4,  1.5,  0.4],
        [ 5.2,  4.1,  1.5,  0.1],
        [ 5.5,  4.2,  1.4,  0.2],
        [ 4.9,  3.1,  1.5,  0.1],
        [ 5. ,  3.2,  1.2,  0.2],
        [ 5.5,  3.5,  1.3,  0.2],
        [ 4.9,  3.1,  1.5,  0.1],
        [ 4.4,  3. ,  1.3,  0.2],
        [ 5.1,  3.4,  1.5,  0.2],
        [ 5. ,  3.5,  1.3,  0.3],
        [ 4.5,  2.3,  1.3,  0.3],
        [ 4.4,  3.2,  1.3,  0.2],
        [ 5. ,  3.5,  1.6,  0.6],
        [ 5.1,  3.8,  1.9,  0.4],
        [ 4.8,  3. ,  1.4,  0.3],
        [ 5.1,  3.8,  1.6,  0.2],
        [ 4.6,  3.2,  1.4,  0.2],
        [ 5.3,  3.7,  1.5,  0.2],
        [ 5. ,  3.3,  1.4,  0.2],
        [ 7. ,  3.2,  4.7,  1.4],
        [ 6.4,  3.2,  4.5,  1.5],
        [ 6.9,  3.1,  4.9,  1.5],
        [ 5.5,  2.3,  4. ,  1.3],
        [ 6.5,  2.8,  4.6,  1.5],
        [ 5.7,  2.8,  4.5,  1.3],
        [ 6.3,  3.3,  4.7,  1.6],
        [ 4.9,  2.4,  3.3,  1. ],
        [ 6.6,  2.9,  4.6,  1.3],
        [ 5.2,  2.7,  3.9,  1.4],
        [ 5. ,  2. ,  3.5,  1. ],
        [ 5.9,  3. ,  4.2,  1.5],
        [ 6. ,  2.2,  4. ,  1. ],
        [ 6.1,  2.9,  4.7,  1.4],
        [ 5.6,  2.9,  3.6,  1.3],
        [ 6.7,  3.1,  4.4,  1.4],
        [ 5.6,  3. ,  4.5,  1.5],
        [ 5.8,  2.7,  4.1,  1. ],
        [ 6.2,  2.2,  4.5,  1.5],
        [ 5.6,  2.5,  3.9,  1.1],
        [ 5.9,  3.2,  4.8,  1.8],
        [ 6.1,  2.8,  4. ,  1.3],
        [ 6.3,  2.5,  4.9,  1.5],
        [ 6.1,  2.8,  4.7,  1.2],
        [ 6.4,  2.9,  4.3,  1.3],
        [ 6.6,  3. ,  4.4,  1.4],
        [ 6.8,  2.8,  4.8,  1.4],
        [ 6.7,  3. ,  5. ,  1.7],
        [ 6. ,  2.9,  4.5,  1.5],
        [ 5.7,  2.6,  3.5,  1. ],
        [ 5.5,  2.4,  3.8,  1.1],
        [ 5.5,  2.4,  3.7,  1. ],
        [ 5.8,  2.7,  3.9,  1.2],
        [ 6. ,  2.7,  5.1,  1.6],
        [ 5.4,  3. ,  4.5,  1.5],
        [ 6. ,  3.4,  4.5,  1.6],
        [ 6.7,  3.1,  4.7,  1.5],
        [ 6.3,  2.3,  4.4,  1.3],
        [ 5.6,  3. ,  4.1,  1.3],
        [ 5.5,  2.5,  4. ,  1.3],
        [ 5.5,  2.6,  4.4,  1.2],
        [ 6.1,  3. ,  4.6,  1.4],
        [ 5.8,  2.6,  4. ,  1.2],
        [ 5. ,  2.3,  3.3,  1. ],
        [ 5.6,  2.7,  4.2,  1.3],
        [ 5.7,  3. ,  4.2,  1.2],
        [ 5.7,  2.9,  4.2,  1.3],
        [ 6.2,  2.9,  4.3,  1.3],
        [ 5.1,  2.5,  3. ,  1.1],
        [ 5.7,  2.8,  4.1,  1.3],
        [ 6.3,  3.3,  6. ,  2.5],
        [ 5.8,  2.7,  5.1,  1.9],
        [ 7.1,  3. ,  5.9,  2.1],
        [ 6.3,  2.9,  5.6,  1.8],
        [ 6.5,  3. ,  5.8,  2.2],
        [ 7.6,  3. ,  6.6,  2.1],
        [ 4.9,  2.5,  4.5,  1.7],
        [ 7.3,  2.9,  6.3,  1.8],
        [ 6.7,  2.5,  5.8,  1.8],
        [ 7.2,  3.6,  6.1,  2.5],
        [ 6.5,  3.2,  5.1,  2. ],
        [ 6.4,  2.7,  5.3,  1.9],
        [ 6.8,  3. ,  5.5,  2.1],
        [ 5.7,  2.5,  5. ,  2. ],
        [ 5.8,  2.8,  5.1,  2.4],
        [ 6.4,  3.2,  5.3,  2.3],
        [ 6.5,  3. ,  5.5,  1.8],
        [ 7.7,  3.8,  6.7,  2.2],
        [ 7.7,  2.6,  6.9,  2.3],
        [ 6. ,  2.2,  5. ,  1.5],
        [ 6.9,  3.2,  5.7,  2.3],
        [ 5.6,  2.8,  4.9,  2. ],
        [ 7.7,  2.8,  6.7,  2. ],
        [ 6.3,  2.7,  4.9,  1.8],
        [ 6.7,  3.3,  5.7,  2.1],
        [ 7.2,  3.2,  6. ,  1.8],
        [ 6.2,  2.8,  4.8,  1.8],
        [ 6.1,  3. ,  4.9,  1.8],
        [ 6.4,  2.8,  5.6,  2.1],
        [ 7.2,  3. ,  5.8,  1.6],
        [ 7.4,  2.8,  6.1,  1.9],
        [ 7.9,  3.8,  6.4,  2. ],
        [ 6.4,  2.8,  5.6,  2.2],
        [ 6.3,  2.8,  5.1,  1.5],
        [ 6.1,  2.6,  5.6,  1.4],
        [ 7.7,  3. ,  6.1,  2.3],
        [ 6.3,  3.4,  5.6,  2.4],
        [ 6.4,  3.1,  5.5,  1.8],
        [ 6. ,  3. ,  4.8,  1.8],
        [ 6.9,  3.1,  5.4,  2.1],
        [ 6.7,  3.1,  5.6,  2.4],
        [ 6.9,  3.1,  5.1,  2.3],
        [ 5.8,  2.7,  5.1,  1.9],
        [ 6.8,  3.2,  5.9,  2.3],
        [ 6.7,  3.3,  5.7,  2.5],
        [ 6.7,  3. ,  5.2,  2.3],
        [ 6.3,  2.5,  5. ,  1.9],
        [ 6.5,  3. ,  5.2,  2. ],
        [ 6.2,  3.4,  5.4,  2.3],
        [ 5.9,  3. ,  5.1,  1.8]]),
 'feature_names': ['sepal length (cm)',
  'sepal width (cm)',
  'petal length (cm)',
  'petal width (cm)'],
 'target': array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
        0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
        1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
        1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
        2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
        2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]),
 'target_names': array(['setosa', 'versicolor', 'virginica'], 
       dtype='<U10')}

In [95]:
iris.keys()


Out[95]:
dict_keys(['DESCR', 'target_names', 'target', 'feature_names', 'data'])

In [96]:
#extract our x and y
x = iris.data[:,2:] 
y = iris.target

In [97]:
#we merge them
my_data = np.column_stack([x,y])

In [98]:
my_data


Out[98]:
array([[ 1.4,  0.2,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 1.3,  0.2,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 1.7,  0.4,  0. ],
       [ 1.4,  0.3,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 1.5,  0.1,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 1.6,  0.2,  0. ],
       [ 1.4,  0.1,  0. ],
       [ 1.1,  0.1,  0. ],
       [ 1.2,  0.2,  0. ],
       [ 1.5,  0.4,  0. ],
       [ 1.3,  0.4,  0. ],
       [ 1.4,  0.3,  0. ],
       [ 1.7,  0.3,  0. ],
       [ 1.5,  0.3,  0. ],
       [ 1.7,  0.2,  0. ],
       [ 1.5,  0.4,  0. ],
       [ 1. ,  0.2,  0. ],
       [ 1.7,  0.5,  0. ],
       [ 1.9,  0.2,  0. ],
       [ 1.6,  0.2,  0. ],
       [ 1.6,  0.4,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 1.6,  0.2,  0. ],
       [ 1.6,  0.2,  0. ],
       [ 1.5,  0.4,  0. ],
       [ 1.5,  0.1,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 1.5,  0.1,  0. ],
       [ 1.2,  0.2,  0. ],
       [ 1.3,  0.2,  0. ],
       [ 1.5,  0.1,  0. ],
       [ 1.3,  0.2,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 1.3,  0.3,  0. ],
       [ 1.3,  0.3,  0. ],
       [ 1.3,  0.2,  0. ],
       [ 1.6,  0.6,  0. ],
       [ 1.9,  0.4,  0. ],
       [ 1.4,  0.3,  0. ],
       [ 1.6,  0.2,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 4.7,  1.4,  1. ],
       [ 4.5,  1.5,  1. ],
       [ 4.9,  1.5,  1. ],
       [ 4. ,  1.3,  1. ],
       [ 4.6,  1.5,  1. ],
       [ 4.5,  1.3,  1. ],
       [ 4.7,  1.6,  1. ],
       [ 3.3,  1. ,  1. ],
       [ 4.6,  1.3,  1. ],
       [ 3.9,  1.4,  1. ],
       [ 3.5,  1. ,  1. ],
       [ 4.2,  1.5,  1. ],
       [ 4. ,  1. ,  1. ],
       [ 4.7,  1.4,  1. ],
       [ 3.6,  1.3,  1. ],
       [ 4.4,  1.4,  1. ],
       [ 4.5,  1.5,  1. ],
       [ 4.1,  1. ,  1. ],
       [ 4.5,  1.5,  1. ],
       [ 3.9,  1.1,  1. ],
       [ 4.8,  1.8,  1. ],
       [ 4. ,  1.3,  1. ],
       [ 4.9,  1.5,  1. ],
       [ 4.7,  1.2,  1. ],
       [ 4.3,  1.3,  1. ],
       [ 4.4,  1.4,  1. ],
       [ 4.8,  1.4,  1. ],
       [ 5. ,  1.7,  1. ],
       [ 4.5,  1.5,  1. ],
       [ 3.5,  1. ,  1. ],
       [ 3.8,  1.1,  1. ],
       [ 3.7,  1. ,  1. ],
       [ 3.9,  1.2,  1. ],
       [ 5.1,  1.6,  1. ],
       [ 4.5,  1.5,  1. ],
       [ 4.5,  1.6,  1. ],
       [ 4.7,  1.5,  1. ],
       [ 4.4,  1.3,  1. ],
       [ 4.1,  1.3,  1. ],
       [ 4. ,  1.3,  1. ],
       [ 4.4,  1.2,  1. ],
       [ 4.6,  1.4,  1. ],
       [ 4. ,  1.2,  1. ],
       [ 3.3,  1. ,  1. ],
       [ 4.2,  1.3,  1. ],
       [ 4.2,  1.2,  1. ],
       [ 4.2,  1.3,  1. ],
       [ 4.3,  1.3,  1. ],
       [ 3. ,  1.1,  1. ],
       [ 4.1,  1.3,  1. ],
       [ 6. ,  2.5,  2. ],
       [ 5.1,  1.9,  2. ],
       [ 5.9,  2.1,  2. ],
       [ 5.6,  1.8,  2. ],
       [ 5.8,  2.2,  2. ],
       [ 6.6,  2.1,  2. ],
       [ 4.5,  1.7,  2. ],
       [ 6.3,  1.8,  2. ],
       [ 5.8,  1.8,  2. ],
       [ 6.1,  2.5,  2. ],
       [ 5.1,  2. ,  2. ],
       [ 5.3,  1.9,  2. ],
       [ 5.5,  2.1,  2. ],
       [ 5. ,  2. ,  2. ],
       [ 5.1,  2.4,  2. ],
       [ 5.3,  2.3,  2. ],
       [ 5.5,  1.8,  2. ],
       [ 6.7,  2.2,  2. ],
       [ 6.9,  2.3,  2. ],
       [ 5. ,  1.5,  2. ],
       [ 5.7,  2.3,  2. ],
       [ 4.9,  2. ,  2. ],
       [ 6.7,  2. ,  2. ],
       [ 4.9,  1.8,  2. ],
       [ 5.7,  2.1,  2. ],
       [ 6. ,  1.8,  2. ],
       [ 4.8,  1.8,  2. ],
       [ 4.9,  1.8,  2. ],
       [ 5.6,  2.1,  2. ],
       [ 5.8,  1.6,  2. ],
       [ 6.1,  1.9,  2. ],
       [ 6.4,  2. ,  2. ],
       [ 5.6,  2.2,  2. ],
       [ 5.1,  1.5,  2. ],
       [ 5.6,  1.4,  2. ],
       [ 6.1,  2.3,  2. ],
       [ 5.6,  2.4,  2. ],
       [ 5.5,  1.8,  2. ],
       [ 4.8,  1.8,  2. ],
       [ 5.4,  2.1,  2. ],
       [ 5.6,  2.4,  2. ],
       [ 5.1,  2.3,  2. ],
       [ 5.1,  1.9,  2. ],
       [ 5.9,  2.3,  2. ],
       [ 5.7,  2.5,  2. ],
       [ 5.2,  2.3,  2. ],
       [ 5. ,  1.9,  2. ],
       [ 5.2,  2. ,  2. ],
       [ 5.4,  2.3,  2. ],
       [ 5.1,  1.8,  2. ]])

In [99]:
#we shuffle the dataset
np.random.shuffle(my_data)

In [100]:
#let's check if the data looks different now..
my_data


Out[100]:
array([[ 1.5,  0.4,  0. ],
       [ 4.9,  2. ,  2. ],
       [ 4.5,  1.5,  1. ],
       [ 1.4,  0.2,  0. ],
       [ 5.9,  2.1,  2. ],
       [ 5.8,  1.6,  2. ],
       [ 1.2,  0.2,  0. ],
       [ 3.9,  1.1,  1. ],
       [ 3.6,  1.3,  1. ],
       [ 4.1,  1.3,  1. ],
       [ 1.6,  0.2,  0. ],
       [ 6.7,  2. ,  2. ],
       [ 5.2,  2.3,  2. ],
       [ 5.3,  2.3,  2. ],
       [ 3. ,  1.1,  1. ],
       [ 5. ,  1.9,  2. ],
       [ 1.3,  0.4,  0. ],
       [ 5.6,  2.4,  2. ],
       [ 5.5,  1.8,  2. ],
       [ 4.3,  1.3,  1. ],
       [ 5.4,  2.3,  2. ],
       [ 1.5,  0.1,  0. ],
       [ 1.9,  0.4,  0. ],
       [ 6. ,  2.5,  2. ],
       [ 1.4,  0.2,  0. ],
       [ 5.6,  2.4,  2. ],
       [ 1.5,  0.1,  0. ],
       [ 3.5,  1. ,  1. ],
       [ 4.3,  1.3,  1. ],
       [ 1.3,  0.3,  0. ],
       [ 1.6,  0.2,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 4.2,  1.3,  1. ],
       [ 1. ,  0.2,  0. ],
       [ 5.6,  2.1,  2. ],
       [ 1.4,  0.3,  0. ],
       [ 4.7,  1.4,  1. ],
       [ 1.6,  0.2,  0. ],
       [ 3.9,  1.4,  1. ],
       [ 1.7,  0.5,  0. ],
       [ 6.6,  2.1,  2. ],
       [ 4.6,  1.5,  1. ],
       [ 4.2,  1.3,  1. ],
       [ 6.1,  2.5,  2. ],
       [ 4.8,  1.8,  1. ],
       [ 4. ,  1.3,  1. ],
       [ 5. ,  2. ,  2. ],
       [ 4. ,  1.3,  1. ],
       [ 4.1,  1. ,  1. ],
       [ 6. ,  1.8,  2. ],
       [ 1.5,  0.2,  0. ],
       [ 1.4,  0.1,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 4.1,  1.3,  1. ],
       [ 4.7,  1.5,  1. ],
       [ 1.5,  0.4,  0. ],
       [ 1.5,  0.1,  0. ],
       [ 1.6,  0.2,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 1.7,  0.2,  0. ],
       [ 6.7,  2.2,  2. ],
       [ 4.4,  1.2,  1. ],
       [ 1.7,  0.4,  0. ],
       [ 4. ,  1.3,  1. ],
       [ 1.3,  0.2,  0. ],
       [ 4.5,  1.5,  1. ],
       [ 5.3,  1.9,  2. ],
       [ 3.5,  1. ,  1. ],
       [ 4.8,  1.8,  2. ],
       [ 4.9,  1.5,  1. ],
       [ 5.5,  1.8,  2. ],
       [ 1.4,  0.2,  0. ],
       [ 1.3,  0.2,  0. ],
       [ 3.7,  1. ,  1. ],
       [ 6.4,  2. ,  2. ],
       [ 1.9,  0.2,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 1.5,  0.3,  0. ],
       [ 5.8,  2.2,  2. ],
       [ 5.9,  2.3,  2. ],
       [ 4.5,  1.5,  1. ],
       [ 4.7,  1.6,  1. ],
       [ 4.9,  1.5,  1. ],
       [ 6.3,  1.8,  2. ],
       [ 4.6,  1.3,  1. ],
       [ 1.6,  0.4,  0. ],
       [ 4.5,  1.3,  1. ],
       [ 1.7,  0.3,  0. ],
       [ 1.2,  0.2,  0. ],
       [ 5.8,  1.8,  2. ],
       [ 4.7,  1.4,  1. ],
       [ 4.5,  1.5,  1. ],
       [ 4.5,  1.5,  1. ],
       [ 5.1,  1.9,  2. ],
       [ 1.6,  0.2,  0. ],
       [ 4.9,  1.8,  2. ],
       [ 1.4,  0.2,  0. ],
       [ 6.1,  1.9,  2. ],
       [ 1.3,  0.3,  0. ],
       [ 5.1,  1.6,  1. ],
       [ 1.4,  0.3,  0. ],
       [ 4.8,  1.4,  1. ],
       [ 5.6,  1.4,  2. ],
       [ 5. ,  1.7,  1. ],
       [ 6.9,  2.3,  2. ],
       [ 1.6,  0.6,  0. ],
       [ 4.5,  1.6,  1. ],
       [ 6.1,  2.3,  2. ],
       [ 4.8,  1.8,  2. ],
       [ 1.1,  0.1,  0. ],
       [ 3.9,  1.2,  1. ],
       [ 1.3,  0.2,  0. ],
       [ 4.7,  1.2,  1. ],
       [ 1.4,  0.3,  0. ],
       [ 4.2,  1.2,  1. ],
       [ 4.4,  1.4,  1. ],
       [ 4.4,  1.4,  1. ],
       [ 1.5,  0.4,  0. ],
       [ 4.9,  1.8,  2. ],
       [ 5.5,  2.1,  2. ],
       [ 5.2,  2. ,  2. ],
       [ 4.2,  1.5,  1. ],
       [ 5.7,  2.3,  2. ],
       [ 5.1,  2. ,  2. ],
       [ 5.6,  1.8,  2. ],
       [ 1.3,  0.2,  0. ],
       [ 4. ,  1. ,  1. ],
       [ 4. ,  1.2,  1. ],
       [ 3.3,  1. ,  1. ],
       [ 5.7,  2.1,  2. ],
       [ 5.4,  2.1,  2. ],
       [ 5.6,  2.2,  2. ],
       [ 4.5,  1.7,  2. ],
       [ 5. ,  1.5,  2. ],
       [ 1.5,  0.1,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 5.1,  1.5,  2. ],
       [ 1.5,  0.2,  0. ],
       [ 5.1,  2.3,  2. ],
       [ 5.1,  1.9,  2. ],
       [ 4.4,  1.3,  1. ],
       [ 1.4,  0.2,  0. ],
       [ 3.3,  1. ,  1. ],
       [ 5.1,  2.4,  2. ],
       [ 1.5,  0.2,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 5.7,  2.5,  2. ],
       [ 4.6,  1.4,  1. ],
       [ 5.1,  1.8,  2. ],
       [ 3.8,  1.1,  1. ]])

In [101]:
#this is my attributes array
my_data[:,:2]


Out[101]:
array([[ 1.5,  0.4],
       [ 4.9,  2. ],
       [ 4.5,  1.5],
       [ 1.4,  0.2],
       [ 5.9,  2.1],
       [ 5.8,  1.6],
       [ 1.2,  0.2],
       [ 3.9,  1.1],
       [ 3.6,  1.3],
       [ 4.1,  1.3],
       [ 1.6,  0.2],
       [ 6.7,  2. ],
       [ 5.2,  2.3],
       [ 5.3,  2.3],
       [ 3. ,  1.1],
       [ 5. ,  1.9],
       [ 1.3,  0.4],
       [ 5.6,  2.4],
       [ 5.5,  1.8],
       [ 4.3,  1.3],
       [ 5.4,  2.3],
       [ 1.5,  0.1],
       [ 1.9,  0.4],
       [ 6. ,  2.5],
       [ 1.4,  0.2],
       [ 5.6,  2.4],
       [ 1.5,  0.1],
       [ 3.5,  1. ],
       [ 4.3,  1.3],
       [ 1.3,  0.3],
       [ 1.6,  0.2],
       [ 1.5,  0.2],
       [ 4.2,  1.3],
       [ 1. ,  0.2],
       [ 5.6,  2.1],
       [ 1.4,  0.3],
       [ 4.7,  1.4],
       [ 1.6,  0.2],
       [ 3.9,  1.4],
       [ 1.7,  0.5],
       [ 6.6,  2.1],
       [ 4.6,  1.5],
       [ 4.2,  1.3],
       [ 6.1,  2.5],
       [ 4.8,  1.8],
       [ 4. ,  1.3],
       [ 5. ,  2. ],
       [ 4. ,  1.3],
       [ 4.1,  1. ],
       [ 6. ,  1.8],
       [ 1.5,  0.2],
       [ 1.4,  0.1],
       [ 1.5,  0.2],
       [ 4.1,  1.3],
       [ 4.7,  1.5],
       [ 1.5,  0.4],
       [ 1.5,  0.1],
       [ 1.6,  0.2],
       [ 1.5,  0.2],
       [ 1.7,  0.2],
       [ 6.7,  2.2],
       [ 4.4,  1.2],
       [ 1.7,  0.4],
       [ 4. ,  1.3],
       [ 1.3,  0.2],
       [ 4.5,  1.5],
       [ 5.3,  1.9],
       [ 3.5,  1. ],
       [ 4.8,  1.8],
       [ 4.9,  1.5],
       [ 5.5,  1.8],
       [ 1.4,  0.2],
       [ 1.3,  0.2],
       [ 3.7,  1. ],
       [ 6.4,  2. ],
       [ 1.9,  0.2],
       [ 1.4,  0.2],
       [ 1.5,  0.3],
       [ 5.8,  2.2],
       [ 5.9,  2.3],
       [ 4.5,  1.5],
       [ 4.7,  1.6],
       [ 4.9,  1.5],
       [ 6.3,  1.8],
       [ 4.6,  1.3],
       [ 1.6,  0.4],
       [ 4.5,  1.3],
       [ 1.7,  0.3],
       [ 1.2,  0.2],
       [ 5.8,  1.8],
       [ 4.7,  1.4],
       [ 4.5,  1.5],
       [ 4.5,  1.5],
       [ 5.1,  1.9],
       [ 1.6,  0.2],
       [ 4.9,  1.8],
       [ 1.4,  0.2],
       [ 6.1,  1.9],
       [ 1.3,  0.3],
       [ 5.1,  1.6],
       [ 1.4,  0.3],
       [ 4.8,  1.4],
       [ 5.6,  1.4],
       [ 5. ,  1.7],
       [ 6.9,  2.3],
       [ 1.6,  0.6],
       [ 4.5,  1.6],
       [ 6.1,  2.3],
       [ 4.8,  1.8],
       [ 1.1,  0.1],
       [ 3.9,  1.2],
       [ 1.3,  0.2],
       [ 4.7,  1.2],
       [ 1.4,  0.3],
       [ 4.2,  1.2],
       [ 4.4,  1.4],
       [ 4.4,  1.4],
       [ 1.5,  0.4],
       [ 4.9,  1.8],
       [ 5.5,  2.1],
       [ 5.2,  2. ],
       [ 4.2,  1.5],
       [ 5.7,  2.3],
       [ 5.1,  2. ],
       [ 5.6,  1.8],
       [ 1.3,  0.2],
       [ 4. ,  1. ],
       [ 4. ,  1.2],
       [ 3.3,  1. ],
       [ 5.7,  2.1],
       [ 5.4,  2.1],
       [ 5.6,  2.2],
       [ 4.5,  1.7],
       [ 5. ,  1.5],
       [ 1.5,  0.1],
       [ 1.4,  0.2],
       [ 5.1,  1.5],
       [ 1.5,  0.2],
       [ 5.1,  2.3],
       [ 5.1,  1.9],
       [ 4.4,  1.3],
       [ 1.4,  0.2],
       [ 3.3,  1. ],
       [ 5.1,  2.4],
       [ 1.5,  0.2],
       [ 1.4,  0.2],
       [ 5.7,  2.5],
       [ 4.6,  1.4],
       [ 5.1,  1.8],
       [ 3.8,  1.1]])

In [102]:
my_data


Out[102]:
array([[ 1.5,  0.4,  0. ],
       [ 4.9,  2. ,  2. ],
       [ 4.5,  1.5,  1. ],
       [ 1.4,  0.2,  0. ],
       [ 5.9,  2.1,  2. ],
       [ 5.8,  1.6,  2. ],
       [ 1.2,  0.2,  0. ],
       [ 3.9,  1.1,  1. ],
       [ 3.6,  1.3,  1. ],
       [ 4.1,  1.3,  1. ],
       [ 1.6,  0.2,  0. ],
       [ 6.7,  2. ,  2. ],
       [ 5.2,  2.3,  2. ],
       [ 5.3,  2.3,  2. ],
       [ 3. ,  1.1,  1. ],
       [ 5. ,  1.9,  2. ],
       [ 1.3,  0.4,  0. ],
       [ 5.6,  2.4,  2. ],
       [ 5.5,  1.8,  2. ],
       [ 4.3,  1.3,  1. ],
       [ 5.4,  2.3,  2. ],
       [ 1.5,  0.1,  0. ],
       [ 1.9,  0.4,  0. ],
       [ 6. ,  2.5,  2. ],
       [ 1.4,  0.2,  0. ],
       [ 5.6,  2.4,  2. ],
       [ 1.5,  0.1,  0. ],
       [ 3.5,  1. ,  1. ],
       [ 4.3,  1.3,  1. ],
       [ 1.3,  0.3,  0. ],
       [ 1.6,  0.2,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 4.2,  1.3,  1. ],
       [ 1. ,  0.2,  0. ],
       [ 5.6,  2.1,  2. ],
       [ 1.4,  0.3,  0. ],
       [ 4.7,  1.4,  1. ],
       [ 1.6,  0.2,  0. ],
       [ 3.9,  1.4,  1. ],
       [ 1.7,  0.5,  0. ],
       [ 6.6,  2.1,  2. ],
       [ 4.6,  1.5,  1. ],
       [ 4.2,  1.3,  1. ],
       [ 6.1,  2.5,  2. ],
       [ 4.8,  1.8,  1. ],
       [ 4. ,  1.3,  1. ],
       [ 5. ,  2. ,  2. ],
       [ 4. ,  1.3,  1. ],
       [ 4.1,  1. ,  1. ],
       [ 6. ,  1.8,  2. ],
       [ 1.5,  0.2,  0. ],
       [ 1.4,  0.1,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 4.1,  1.3,  1. ],
       [ 4.7,  1.5,  1. ],
       [ 1.5,  0.4,  0. ],
       [ 1.5,  0.1,  0. ],
       [ 1.6,  0.2,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 1.7,  0.2,  0. ],
       [ 6.7,  2.2,  2. ],
       [ 4.4,  1.2,  1. ],
       [ 1.7,  0.4,  0. ],
       [ 4. ,  1.3,  1. ],
       [ 1.3,  0.2,  0. ],
       [ 4.5,  1.5,  1. ],
       [ 5.3,  1.9,  2. ],
       [ 3.5,  1. ,  1. ],
       [ 4.8,  1.8,  2. ],
       [ 4.9,  1.5,  1. ],
       [ 5.5,  1.8,  2. ],
       [ 1.4,  0.2,  0. ],
       [ 1.3,  0.2,  0. ],
       [ 3.7,  1. ,  1. ],
       [ 6.4,  2. ,  2. ],
       [ 1.9,  0.2,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 1.5,  0.3,  0. ],
       [ 5.8,  2.2,  2. ],
       [ 5.9,  2.3,  2. ],
       [ 4.5,  1.5,  1. ],
       [ 4.7,  1.6,  1. ],
       [ 4.9,  1.5,  1. ],
       [ 6.3,  1.8,  2. ],
       [ 4.6,  1.3,  1. ],
       [ 1.6,  0.4,  0. ],
       [ 4.5,  1.3,  1. ],
       [ 1.7,  0.3,  0. ],
       [ 1.2,  0.2,  0. ],
       [ 5.8,  1.8,  2. ],
       [ 4.7,  1.4,  1. ],
       [ 4.5,  1.5,  1. ],
       [ 4.5,  1.5,  1. ],
       [ 5.1,  1.9,  2. ],
       [ 1.6,  0.2,  0. ],
       [ 4.9,  1.8,  2. ],
       [ 1.4,  0.2,  0. ],
       [ 6.1,  1.9,  2. ],
       [ 1.3,  0.3,  0. ],
       [ 5.1,  1.6,  1. ],
       [ 1.4,  0.3,  0. ],
       [ 4.8,  1.4,  1. ],
       [ 5.6,  1.4,  2. ],
       [ 5. ,  1.7,  1. ],
       [ 6.9,  2.3,  2. ],
       [ 1.6,  0.6,  0. ],
       [ 4.5,  1.6,  1. ],
       [ 6.1,  2.3,  2. ],
       [ 4.8,  1.8,  2. ],
       [ 1.1,  0.1,  0. ],
       [ 3.9,  1.2,  1. ],
       [ 1.3,  0.2,  0. ],
       [ 4.7,  1.2,  1. ],
       [ 1.4,  0.3,  0. ],
       [ 4.2,  1.2,  1. ],
       [ 4.4,  1.4,  1. ],
       [ 4.4,  1.4,  1. ],
       [ 1.5,  0.4,  0. ],
       [ 4.9,  1.8,  2. ],
       [ 5.5,  2.1,  2. ],
       [ 5.2,  2. ,  2. ],
       [ 4.2,  1.5,  1. ],
       [ 5.7,  2.3,  2. ],
       [ 5.1,  2. ,  2. ],
       [ 5.6,  1.8,  2. ],
       [ 1.3,  0.2,  0. ],
       [ 4. ,  1. ,  1. ],
       [ 4. ,  1.2,  1. ],
       [ 3.3,  1. ,  1. ],
       [ 5.7,  2.1,  2. ],
       [ 5.4,  2.1,  2. ],
       [ 5.6,  2.2,  2. ],
       [ 4.5,  1.7,  2. ],
       [ 5. ,  1.5,  2. ],
       [ 1.5,  0.1,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 5.1,  1.5,  2. ],
       [ 1.5,  0.2,  0. ],
       [ 5.1,  2.3,  2. ],
       [ 5.1,  1.9,  2. ],
       [ 4.4,  1.3,  1. ],
       [ 1.4,  0.2,  0. ],
       [ 3.3,  1. ,  1. ],
       [ 5.1,  2.4,  2. ],
       [ 1.5,  0.2,  0. ],
       [ 1.4,  0.2,  0. ],
       [ 5.7,  2.5,  2. ],
       [ 4.6,  1.4,  1. ],
       [ 5.1,  1.8,  2. ],
       [ 3.8,  1.1,  1. ]])

In [103]:
#we figure out how long is our array
array_length= int(len(my_data) / 5)
n= array_length

In [104]:
#then we can divide it in 5 subsets, we found this online, still note sure what each line of code does.
def chunks(l, n):
    n = max(1, n)
    return [l[i:i + n] for i in range(0, len(l), n)]

In [105]:
#now im checking to see if I have 5 subsets by calling the first one.
subsets= chunks(my_data,n)
subsets[1]


Out[105]:
array([[ 1.6,  0.2,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 4.2,  1.3,  1. ],
       [ 1. ,  0.2,  0. ],
       [ 5.6,  2.1,  2. ],
       [ 1.4,  0.3,  0. ],
       [ 4.7,  1.4,  1. ],
       [ 1.6,  0.2,  0. ],
       [ 3.9,  1.4,  1. ],
       [ 1.7,  0.5,  0. ],
       [ 6.6,  2.1,  2. ],
       [ 4.6,  1.5,  1. ],
       [ 4.2,  1.3,  1. ],
       [ 6.1,  2.5,  2. ],
       [ 4.8,  1.8,  1. ],
       [ 4. ,  1.3,  1. ],
       [ 5. ,  2. ,  2. ],
       [ 4. ,  1.3,  1. ],
       [ 4.1,  1. ,  1. ],
       [ 6. ,  1.8,  2. ],
       [ 1.5,  0.2,  0. ],
       [ 1.4,  0.1,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 4.1,  1.3,  1. ],
       [ 4.7,  1.5,  1. ],
       [ 1.5,  0.4,  0. ],
       [ 1.5,  0.1,  0. ],
       [ 1.6,  0.2,  0. ],
       [ 1.5,  0.2,  0. ],
       [ 1.7,  0.2,  0. ]])

In [106]:
subsets[0][:,2:]


Out[106]:
array([[ 0.],
       [ 2.],
       [ 1.],
       [ 0.],
       [ 2.],
       [ 2.],
       [ 0.],
       [ 1.],
       [ 1.],
       [ 1.],
       [ 0.],
       [ 2.],
       [ 2.],
       [ 2.],
       [ 1.],
       [ 2.],
       [ 0.],
       [ 2.],
       [ 2.],
       [ 1.],
       [ 2.],
       [ 0.],
       [ 0.],
       [ 2.],
       [ 0.],
       [ 2.],
       [ 0.],
       [ 1.],
       [ 1.],
       [ 0.]])

In [107]:
dt = tree.DecisionTreeClassifier()

In [108]:
# for the following part I must give credit to Barney! He was the one who figured it out.

In [111]:
average_list = []
for item in subsets:
    x_chunks= item[:,:2]
    y_chunks= item[:,2:]
    for x, y in zip(x_chunks, y_chunks):
        x_test = list(x_chunks).pop(0)
        x_train = x_chunks[:]   #sum(x_chunks, [])
        list(x_chunks).append(x_test)
        
        y_test = list(y_chunks).pop(0)
        y_train = y_chunks[:]#sum(y_chunks, [])
        list(y_chunks).append(y_test)
        #print("trainers: ", x_train, y_train)
        dt = dt.fit(x_train,y_train)
        y_pred= dt.predict(x_test)
accuracy = metrics.accuracy_score(y_test, y_pred)
average_list.append(accuracy)   
print(average_list)


[1.0]
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)
/usr/local/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
  DeprecationWarning)

In [ ]: