com.datumbox.framework.core.machinelearning.modelselection.metrics

Class LinearRegressionMetrics

java.lang.Object

com.datumbox.framework.core.machinelearning.common.abstracts.modelselection.AbstractMetrics

com.datumbox.framework.core.machinelearning.modelselection.metrics.LinearRegressionMetrics

All Implemented Interfaces:

ValidationMetrics, java.io.Serializable

public class LinearRegressionMetrics
extends AbstractMetrics

Validation class for Linear Regression.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
LinearRegressionMetrics(Dataframe predictedData)
LinearRegressionMetrics(java.util.List<LinearRegressionMetrics> validationMetricsList)

Method Summary

Modifier and Type	Method and Description
double	getDfRegression() Getter for the degrees of freedom of Regression.
double	getDfResidual() Getter for the degrees of freedom of Residual.
double	getDfTotal() Getter for the degrees of freedom of Total.
double	getDW() Getter of Durbin Watson statistic.
double	getF() Getter for F score.
double	getFPValue() Getter for F p-value.
double	getNormalResiduals() Getter for Normal Residuals.
double	getRSquare() Getter for the R Square.
double	getRSquareAdjusted() Getter for the R Square Adjusted.
double	getSSE() Getter for the Sum of Squared Errors.
double	getSSR() Getter for the Sum of Squared due to Regression.
double	getSST() Getter for the Sum of Squared Total.
double	getStdErrorOfEstimate() Getter for Standard Error of Estimate.
java.lang.String	toString()

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface com.datumbox.framework.core.machinelearning.common.interfaces.ValidationMetrics

newInstance, newInstance, newInstance

Constructor Detail

LinearRegressionMetrics

public LinearRegressionMetrics(Dataframe predictedData)

Parameters:

predictedData -

See Also:

AbstractMetrics.AbstractMetrics(Dataframe)

LinearRegressionMetrics

public LinearRegressionMetrics(java.util.List<LinearRegressionMetrics> validationMetricsList)

Parameters:

validationMetricsList -

See Also:

AbstractMetrics.AbstractMetrics(List)

Method Detail

getRSquare

public double getRSquare()

Getter for the R Square.

Returns:

getRSquareAdjusted

public double getRSquareAdjusted()

Getter for the R Square Adjusted.

Returns:

getSSE

public double getSSE()

Getter for the Sum of Squared Errors.

Returns:

getSSR

public double getSSR()

Getter for the Sum of Squared due to Regression.

Returns:

getSST

public double getSST()

Getter for the Sum of Squared Total.

Returns:

getDfRegression

public double getDfRegression()

Getter for the degrees of freedom of Regression.

Returns:

getDfResidual

public double getDfResidual()

Getter for the degrees of freedom of Residual.

Returns:

getDfTotal

public double getDfTotal()

Getter for the degrees of freedom of Total.

Returns:

getF

public double getF()

Getter for F score.

Returns:

getFPValue

public double getFPValue()

Getter for F p-value.

Returns:

getStdErrorOfEstimate

public double getStdErrorOfEstimate()

Getter for Standard Error of Estimate.

Returns:

getDW

public double getDW()

Getter of Durbin Watson statistic.

Returns:

getNormalResiduals

public double getNormalResiduals()

Getter for Normal Residuals.

Returns:

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object