ML.EVAL.REGRESSION.D2_TWEEDIE_SCORE

Returns the D^2 regression score function, fraction of Tweedie deviance explained.

Syntax

ML.EVAL.REGRESSION.D2_TWEEDIE_SCORE(y_true, y_pred, sample_weight, power)

Arguments

Name	Type	Default	Description
y_true	object		DataFrame or array object of ground-truth target values.
y_pred	object		DataFrame or array object of predicted target values.
sample_weight	Any	None	Optional DataFrame or array object of per-sample weights. Omit for uniform weights.
power	Any	0	Tweedie power parameter. 0 = normal, 1 = Poisson, 2 = Gamma, 3 = inverse Gaussian; values in (1, 2) correspond to compound Poisson.

Examples

Examples coming soon

Working Excel formula examples for this function are not yet written.

See also

• ML.EVAL.REGRESSION.D2_ABSOLUTE_ERROR_SCORE
• ML.EVAL.REGRESSION.D2_PINBALL_SCORE
• ML.EVAL.REGRESSION.EXPLAINED_VARIANCE_SCORE
• ML.EVAL.REGRESSION.MAX_ERROR
• ML.EVAL.REGRESSION.MEAN_ABSOLUTE_ERROR
• ML.EVAL.REGRESSION.MEAN_ABSOLUTE_PERCENTAGE_ERROR
• ML.EVAL.REGRESSION.MEAN_GAMMA_DEVIANCE
• ML.EVAL.REGRESSION.MEAN_POISSON_DEVIANCE
• ML.EVAL.REGRESSION.MEAN_SQUARED_ERROR
• ML.EVAL.REGRESSION.MEAN_SQUARED_LOG_ERROR
• ML.EVAL.REGRESSION.MEDIAN_ABSOLUTE_ERROR
• ML.EVAL.REGRESSION.R2_SCORE
• ML.EVAL.REGRESSION.ROOT_MEAN_SQUARED_ERROR
• ML.EVAL.REGRESSION.ROOT_MEAN_SQUARED_LOG_ERROR