h2o-py/h2o/model/regression.py
def h2o_explained_variance_score(y_actual, y_predicted, weights=None):
    """
    Explained variance regression score function.

    :param y_actual: H2OFrame of actual response.
    :param y_predicted: H2OFrame of predicted response.
    :param weights: (Optional) sample weights
    :returns: the explained variance score.
    """
    ModelBase._check_targets(y_actual, y_predicted)

    _, numerator = _mean_var(y_actual - y_predicted, weights)
    _, denominator = _mean_var(y_actual, weights)
    if denominator == 0.0:
        return 1. if numerator == 0 else 0.  # 0/0 => 1, otherwise, 0
    return 1 - numerator / denominator
def h2o_explained_variance_score(y_actual, y_predicted, weights=None):
    ModelBase._check_targets(y_actual, y_predicted)

    _, numerator = _mean_var(y_actual - y_predicted, weights)
    _, denominator = _mean_var(y_actual, weights)
    if denominator == 0.0:
        return 1. if numerator == 0 else 0.  # 0/0 => 1, otherwise, 0
    return 1 - numerator / denominator
def h2o_explained_variance_score ( y_actual , y_predicted , weights = None ) : ModelBase . _check_targets ( y_actual , y_predicted ) _ , numerator = _mean_var ( y_actual - y_predicted , weights ) _ , denominator = _mean_var ( y_actual , weights ) if denominator == 0.0 : return 1. if numerator == 0 else 0. # 0/0 => 1, otherwise, 0 return 1 - numerator / denominator
Explained variance regression score function.

    :param y_actual: H2OFrame of actual response.
    :param y_predicted: H2OFrame of predicted response.
    :param weights: (Optional) sample weights
    :returns: the explained variance score.
Explained variance regression score function .