#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 12 12:30:56 2018

@author: auri
"""

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

dataset = pd.read_csv('combined.csv')
X = dataset.iloc[:, 0:9].values
y = dataset.iloc[:, 9].values

#y = pd.DataFrame(y)

from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_y = LabelEncoder()
y[:, 0] = labelencoder_y.fit_transform(y[:, 0])
onehotencoder = OneHotEncoder(categorical_features = [0])
X = onehotencoder.fit_transform(X).toarray()
# Encoding the Dependent Variable
labelencoder_y = LabelEncoder()
y = labelencoder_y.fit_transform(y)
f4220e9ab5f5f8307d31c09b60bae79f19b00bad
<mask token>

<mask token>
dataset = pd.read_csv('combined.csv')
X = dataset.iloc[:, 0:9].values
y = dataset.iloc[:, 9].values
<mask token>
labelencoder_y = LabelEncoder()
y[:, 0] = labelencoder_y.fit_transform(y[:, 0])
onehotencoder = OneHotEncoder(categorical_features=[0])
X = onehotencoder.fit_transform(X).toarray()
labelencoder_y = LabelEncoder()
y = labelencoder_y.fit_transform(y)

<mask token>
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
dataset = pd.read_csv('combined.csv')
X = dataset.iloc[:, 0:9].values
y = dataset.iloc[:, 9].values
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_y = LabelEncoder()
y[:, 0] = labelencoder_y.fit_transform(y[:, 0])
onehotencoder = OneHotEncoder(categorical_features=[0])
X = onehotencoder.fit_transform(X).toarray()
labelencoder_y = LabelEncoder()
y = labelencoder_y.fit_transform(y)

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 12 12:30:56 2018

@author: auri
"""

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

dataset = pd.read_csv('combined.csv')
X = dataset.iloc[:, 0:9].values
y = dataset.iloc[:, 9].values

#y = pd.DataFrame(y)

from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_y = LabelEncoder()
y[:, 0] = labelencoder_y.fit_transform(y[:, 0])
onehotencoder = OneHotEncoder(categorical_features = [0])
X = onehotencoder.fit_transform(X).toarray()
# Encoding the Dependent Variable
labelencoder_y = LabelEncoder()
y = labelencoder_y.fit_transform(y)