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gkhayes/Iris_Preprocessing.py

Created January 21, 2019 06:53
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Pre-process the Iris dataset
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Iris_Preprocessing.py
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler, OneHotEncoder
# Split data into training and test sets
X_train, X_test, y_train, y_test = train_test_split(data.data, data.target,
test_size = 0.2, random_state = 3)
# Normalize feature data
scaler = MinMaxScaler()
X_train_scaled = scaler.fit_transform(X_train)
X_test_scaled = scaler.transform(X_test)
# One hot encode target values
one_hot = OneHotEncoder()
y_train_hot = one_hot.fit_transform(y_train.reshape(-1, 1)).todense()
y_test_hot = one_hot.transform(y_test.reshape(-1, 1)).todense()
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