SimpleLinearRegressionCoefficientOfDetermination Method (Double, Double, Boolean, Double)

public double CoefficientOfDetermination(
	double[] inputs,
	double[] outputs,
	bool adjust,
	double[] weights = null
)

Public Function CoefficientOfDetermination ( 
	inputs As Double(),
	outputs As Double(),
	adjust As Boolean,
	Optional weights As Double() = Nothing
) As Double

Parameters

inputs

Type: SystemDouble

outputs

Type: SystemDouble

adjust

Type: SystemBoolean

weights (Optional)

Type: SystemDouble

Return Value

The coefficient of determination is used in the context of statistical models whose main purpose is the prediction of future outcomes on the basis of other related information. It is the proportion of variability in a data set that is accounted for by the statistical model. It provides a measure of how well future outcomes are likely to be predicted by the model.

The R² coefficient of determination is a statistical measure of how well the regression line approximates the real data points. An R² of 1.0 indicates that the regression line perfectly fits the data.

This method uses the RSquaredLoss class to compute the R² coefficient. Please see the documentation for RSquaredLoss for more details, including usage examples.

Reference