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.TransformerMixinClass 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
- 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