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BinarySpoon/Log Transformation.py Secret

Created November 3, 2020 13:29
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Log Transformation.py
# Log transformation -->
features = ['NOX','PTRATIO','RM','TAX','LSTAT','INDUS']
x_data = boston_data.loc[:,features]
y_label = boston_data['Target']
min_max_scaler = MinMaxScaler()
x_data = pd.DataFrame(data=min_max_scaler.fit_transform(x_data), columns = features)
y_label = np.log1p(y_label)
for features in x_data.columns:
if np.abs(x_data[features].skew()) > 0.5:
x_data[features] = np.log1p(x_data[features])
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