module sklapi.sklearn_base_regressor

Short summary

module mlinsights.sklapi.sklearn_base_regressor

Implements SkBaseRegressor.

source on GitHub

Classes

class	truncated documentation
SkBaseRegressor	Defines a custom regressor.

Methods

method	truncated documentation
__init__	constructor
score	Returns the mean accuracy on the given test data and labels.

Documentation

Implements SkBaseRegressor.

source on GitHub

class mlinsights.sklapi.sklearn_base_regressor.SkBaseRegressor(**kwargs)

Bases: SkBaseLearner

Defines a custom regressor.

source on GitHub

constructor

source on GitHub

__init__(**kwargs)

constructor

source on GitHub

score(X, y=None, sample_weight=None)

Returns the mean accuracy on the given test data and labels.

Parameters:

• X – Training data, numpy array or sparse matrix of shape [n_samples,n_features]

• y – Target values, numpy array of shape [n_samples, n_targets] (optional)

• sample_weight – Weight values, numpy array of shape [n_samples, n_targets] (optional)

Returns:

score : float, Mean accuracy of self.predict(X) wrt. y.

source on GitHub