schrodinger.application.matsci.mlearn.base module

Classes and functions to deal with ML features.

Copyright Schrodinger, LLC. All rights reserved.

class schrodinger.application.matsci.mlearn.base.BaseFeaturizer

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

Class that MUST be inherited to create sklearn Model.

fit(data, data_y=None)

Fit and return self. Anything that evaluates properties related to the passed data should go here. For example, compute physical properties of a stucture and save them as class property, to be used in the transform method.

Parameters:

• data (numpy array of shape [n_samples, n_features]) – Training set
• data_y (numpy array of shape [n_samples]) – Target values

Return type:

BaseFeaturizer

Returns:

self object with fitted data

transform(data)

Get numerical features. Must be implemented by a child class.

Parameters:data (numpy array of shape [n_samples, n_features]) – Training set Return type:numpy array of shape [n_samples, n_features_new] Returns:Transformed array