Mastering Machine Learning with Python in Six Steps by Manohar Swamynathan

Author:Manohar Swamynathan
Language: eng
Format: epub
Publisher: Apress, Berkeley, CA

# create hihger order polynomial for independent variables

order_no = 6

# map the variable 1 & 2 to its higher order polynomial

def map_features(variable_1, variable_2, order=order_no):

assert order >= 1

def iter():

for i in range(1, order + 1):

for j in range(i + 1):

yield np.power(variable_1, i - j) * np.power(variable_2, j)

return np.vstack(iter())

out = map_features(data['x1'], data['x2'], order=order_no)

X = out.transpose()

y = data['class']

# split the data into train and test

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=0)

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