PolynomialFeatures

class mastml.legos.feature_generators.PolynomialFeatures(features=None, degree=2, interaction_only=False, include_bias=True)

Bases: sklearn.base.BaseEstimator, sklearn.base.TransformerMixin

Class to generate polynomial features using scikit-learn’s polynomial features method More info at: http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PolynomialFeatures.html

Args:

degree: (int), degree of polynomial features

interaction_only: (bool), If true, only interaction features are produced: features that are products of at most degree distinct input features (so not x[1] ** 2, x[0] * x[2] ** 3, etc.).

include_bias: (bool),If True (default), then include a bias column, the feature in which all polynomial powers are zero (i.e. a column of ones - acts as an intercept term in a linear model).

Methods:

fit: conducts fit method of polynomial feature generation

Args:

df: (dataframe), dataframe of input X and y data

transform: generates dataframe containing polynomial features

Args:

df: (dataframe), dataframe of input X and y data

Returns:

(dataframe), dataframe containing new polynomial features, plus original features present

Methods Summary

fit(df[, y])
transform(df)

Methods Documentation

fit(df, y=None)

transform(df)