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javax.visrec.ml.eval

public Class EvaluationMetrics

Class Inheritance

extends Object

java.lang.Object
javax.visrec.ml.eval.EvaluationMetrics

Known Direct Subclasses

javax.visrec.ml.eval.RegressionMetrics, javax.visrec.ml.eval.ClassificationMetrics

Imports

java.util.HashMap

Wrapper for constants and values for classifier and regressor evaluation metrics.

Field Summary

Modifier and Type	Field and Description
public static final String	ACCURACY
private static final HashMap<String, String>	description
public static final String	F1SCORE
public static final String	F_STAT Is there a relationship between inputs and predictions(outputs) at all.
public static final String	MEAN_ABSOLUTE_ERROR Mean value of sum of squared errors.
public static final String	MEAN_SQUARED_ERROR
public static final String	PRECISION
public static final String	R_SQUARED Percent of variation explained by the regression model.
public static final String	RECALL
public static final String	RESIDUAL_SQUARE_SUM
public static final String	RESIDUAL_STANDARD_ERROR Estimation of standard deviation of prediction errors for some given data set.
public static final String	ROOT_MEAN_SQUARED_ERROR
private final HashMap<String, Float>	values

Constructor Summary

Access	Constructor and Description
public	EvaluationMetrics()

Method Summary

Modifier and Type	Method and Description
public float	get(String key)
public void	set(String key, float value)
public String	toString() Overrides java.lang.Object.toString. Returns a string representation of the object.

Inherited from java.lang.Object:: clone equals finalize getClass hashCode notify notifyAll wait wait wait

Field Detail

ACCURACY	back to summary
public static final String ACCURACY

description	back to summary
private static final HashMap<String, String> description

F1SCORE	back to summary
public static final String F1SCORE

F_STAT	back to summary
public static final String F_STAT Is there a relationship between inputs and predictions(outputs) at all. If there is a relationship, this value is greater then 1. When there is now relationship, this value is around 1.

MEAN_ABSOLUTE_ERROR	back to summary
public static final String MEAN_ABSOLUTE_ERROR Mean value of sum of squared errors. Errors are squared in order to better explain variability, and take into account positive and negative errors. Regression metrics

MEAN_SQUARED_ERROR	back to summary
public static final String MEAN_SQUARED_ERROR

PRECISION	back to summary
public static final String PRECISION

R_SQUARED	back to summary
public static final String R_SQUARED Percent of variation explained by the regression model. 1 is good , 0 is bad, bigger is better.

RECALL	back to summary
public static final String RECALL

RESIDUAL_SQUARE_SUM	back to summary
public static final String RESIDUAL_SQUARE_SUM

RESIDUAL_STANDARD_ERROR	back to summary
public static final String RESIDUAL_STANDARD_ERROR Estimation of standard deviation of prediction errors for some given data set. Smaller is better.

ROOT_MEAN_SQUARED_ERROR	back to summary
public static final String ROOT_MEAN_SQUARED_ERROR

values	back to summary
private final HashMap<String, Float> values

Constructor Detail

EvaluationMetrics	back to summary
public EvaluationMetrics()

Method Detail

get	back to summary
public float get(String key)

set	back to summary
public void set(String key, float value)

toString

back to summary

public String toString()

Overrides java.lang.Object.toString.

Doc from java.lang.Object.toString.

Returns a string representation of the object.

Returns:String

a string representation of the object.

Annotations

@Override