Source code for mlinsights.sklapi.sklearn_base_regressor

from sklearn.metrics import r2_score
from .sklearn_base_learner import SkBaseLearner




class SkBaseRegressor(SkBaseLearner):
    """
    Defines a custom regressor.
    """

    def __init__(self, **kwargs):
        """
        constructor
        """
        SkBaseLearner.__init__(self, **kwargs)



    def score(self, X, y=None, sample_weight=None):
        """
        Returns the mean accuracy on the given test data and labels.

        :param X: Training data, numpy array or sparse matrix of
            shape [n_samples,n_features]
        :param y: Target values, numpy array of shape [n_samples, n_targets] (optional)
        :param sample_weight: Weight values, numpy array of shape
            [n_samples, n_targets] (optional)
        :return: score : float, Mean accuracy of self.predict(X) wrt. y.
        """
        return r2_score(y, self.predict(X), sample_weight=sample_weight)