Uses of Class
org.tribuo.regression.evaluation.RegressionSufficientStatistics

Packages that use RegressionSufficientStatistics

Package	Description
org.tribuo.regression.evaluation	Evaluation classes for single or multi-dimensional regression.

Uses of RegressionSufficientStatistics in org.tribuo.regression.evaluation

Methods in org.tribuo.regression.evaluation with parameters of type RegressionSufficientStatistics

Modifier and Type	Method and Description
static double	RegressionMetrics.explainedVariance(MetricTarget<Regressor> target, RegressionSufficientStatistics sufficientStats) Calculates the explained variance based on the supplied statistics.
static double	RegressionMetrics.explainedVariance(Regressor variable, RegressionSufficientStatistics sufficientStats) Calculates the explained variance based on the supplied statistics for a single dimension.
static double	RegressionMetrics.mae(MetricTarget<Regressor> target, RegressionSufficientStatistics sufficientStats) Calculates the Mean Absolute Error based on the supplied statistics.
static double	RegressionMetrics.mae(Regressor variable, RegressionSufficientStatistics sufficientStats) Calculates the Mean Absolute Error based on the supplied statistics for a single dimension.
static double	RegressionMetrics.r2(MetricTarget<Regressor> target, RegressionSufficientStatistics sufficientStats) Calculates R^2 based on the supplied statistics.
static double	RegressionMetrics.r2(Regressor variable, RegressionSufficientStatistics sufficientStats) Calculates R^2 based on the supplied statistics for a single dimension.
static double	RegressionMetrics.rmse(MetricTarget<Regressor> target, RegressionSufficientStatistics sufficientStats) Calculates the RMSE based on the supplied statistics.
static double	RegressionMetrics.rmse(Regressor variable, RegressionSufficientStatistics sufficientStats) Calculates the RMSE based on the supplied statistics for a single dimension.