Class RegressionMetrics

java.lang.Object

javax.visrec.ml.eval.EvaluationMetrics

deepnetts.eval.RegressionMetrics

public class RegressionMetrics
extends javax.visrec.ml.eval.EvaluationMetrics

Common metrics for regression models.

Field Summary

Fields inherited from class javax.visrec.ml.eval.EvaluationMetrics

ACCURACY, F_STAT, F1SCORE, MEAN_ABSOLUTE_ERROR, MEAN_SQUARED_ERROR, PRECISION, R_SQUARED, RECALL, RESIDUAL_SQUARE_SUM, RESIDUAL_STANDARD_ERROR, ROOT_MEAN_SQUARED_ERROR

Constructor Summary

Constructors

Constructor	Description
RegressionMetrics()

Method Summary

Modifier and Type	Method	Description
float	getFStat()
float	getMaxError()
float	getMeanAbsoluteError()
float	getMeanAbsolutePercentageError()
float	getMeanSquaredError()	Mean squared error is the average value of the sum of squared errors.
float	getR2()	Proportion of variance explained by the model.A value between 0 and 1, where 1 is the best and 0 worst.
float	getResidualStandardError()
float	getRootMeanSquaredError()
float	getSquaredErrorSum()
void	setFStat(float fStat)
void	setMaxError(float maxError)
void	setMeanAbsoluteError(float meanAbsoluteError)
void	setMeanAbsolutePercentageError(float meanAbsolutePercentageError)
void	setMeanSquaredError(float meanSquaredError)
void	setR2(float r2)
void	setResidualStandardError(float residualStandardError)
void	setRootMeanSquaredError(float rootMeanSquaredError)
void	setSquaredErrorSum(float squaredErrorSum)
String	toString()

Methods inherited from class javax.visrec.ml.eval.EvaluationMetrics

get, set

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Details

RegressionMetrics

public RegressionMetrics()

Method Details

getR2

public float getR2()

Proportion of variance explained by the model.A value between 0 and 1, where 1 is the best and 0 worst. Intuitively how much the model prediction is better than using mean value as prediction.

setR2

public void setR2(float r2)

getMeanSquaredError

public float getMeanSquaredError()

Mean squared error is the average value of the sum of squared errors.

setMeanSquaredError

public void setMeanSquaredError(float meanSquaredError)

getRootMeanSquaredError

public float getRootMeanSquaredError()

setRootMeanSquaredError

public void setRootMeanSquaredError(float rootMeanSquaredError)

getMeanAbsoluteError

public float getMeanAbsoluteError()

setMeanAbsoluteError

public void setMeanAbsoluteError(float meanAbsoluteError)

getMeanAbsolutePercentageError

public float getMeanAbsolutePercentageError()

getSquaredErrorSum

public float getSquaredErrorSum()

setSquaredErrorSum

public void setSquaredErrorSum(float squaredErrorSum)

setMeanAbsolutePercentageError

public void setMeanAbsolutePercentageError(float meanAbsolutePercentageError)

getMaxError

public float getMaxError()

setMaxError

public void setMaxError(float maxError)

getResidualStandardError

public float getResidualStandardError()

setResidualStandardError

public void setResidualStandardError(float residualStandardError)

getFStat

public float getFStat()

setFStat

public void setFStat(float fStat)

toString

public String toString()

Overrides:

toString in class javax.visrec.ml.eval.EvaluationMetrics