Package weka.classifiers.evaluation

Class MSLE

java.lang.Object

weka.classifiers.evaluation.AbstractEvaluationMetric

weka.classifiers.evaluation.AbstractSimpleRegressionMeasure

weka.classifiers.evaluation.MSLE

All Implemented Interfaces:

Serializable, weka.classifiers.evaluation.StandardEvaluationMetric

public class MSLE
extends AbstractSimpleRegressionMeasure

Computes the mean squared log error (MSLE) for regression models. Only works with actual values that are greater than 0 due to log.

Author:

FracPete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class weka.classifiers.evaluation.AbstractEvaluationMetric

weka.classifiers.evaluation.AbstractEvaluationMetric.UnknownStatisticException

Field Summary

Fields

Modifier and Type	Field	Description
static double	EPSILON
static String	NAME

Fields inherited from class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure

m_Actual, m_Predicted

Fields inherited from class weka.classifiers.evaluation.AbstractEvaluationMetric

m_baseEvaluation

Constructor Summary

Constructors

Constructor	Description
MSLE()

Method Summary

Modifier and Type	Method	Description
protected double	clip(double value)	Limits the value to EPSILON or larger.
String	getMetricDescription()	Get a short description of this metric (algorithm, forumulas etc.).
String	getMetricName()	Get the name of this metric
double	getStatistic(String statName)	Get the value of the named statistic
List<String>	getStatisticNames()	Get a list of the names of the statistics that this metrics computes.
boolean	statisticIsMaximisable(String statName)	True if the optimum value of the named metric is a maximum value; false if the optimim value is a minimum value.
String	toSummaryString()	Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.

Methods inherited from class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure

appliesToNominalClass, appliesToNumericClass, updateStatsForClassifier, updateStatsForPredictor

Methods inherited from class weka.classifiers.evaluation.AbstractEvaluationMetric

getPluginMetrics, setBaseEvaluation

Methods inherited from class java.lang.Object

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

Field Detail

NAME

public static final String NAME

See Also:

Constant Field Values

EPSILON

public static final double EPSILON

See Also:

Constant Field Values

Constructor Detail

MSLE

public MSLE()

Method Detail

getMetricName

public String getMetricName()

Get the name of this metric

Specified by:

getMetricName in class weka.classifiers.evaluation.AbstractEvaluationMetric

Returns:

the name of this metric

getMetricDescription

public String getMetricDescription()

Get a short description of this metric (algorithm, forumulas etc.).

Specified by:

getMetricDescription in class weka.classifiers.evaluation.AbstractEvaluationMetric

Returns:

a short description of this metric

getStatisticNames

public List<String> getStatisticNames()

Get a list of the names of the statistics that this metrics computes. E.g. an information theoretic evaluation measure might compute total number of bits as well as average bits/instance

Specified by:

getStatisticNames in class weka.classifiers.evaluation.AbstractEvaluationMetric

Returns:

the names of the statistics that this metric computes

clip

protected double clip(double value)

Limits the value to EPSILON or larger.

Parameters:

value - the value to fix

Returns:

the fixed value

getStatistic

public double getStatistic(String statName)

Get the value of the named statistic

Specified by:

getStatistic in class weka.classifiers.evaluation.AbstractEvaluationMetric

Parameters:

statName - the name of the statistic to compute the value for

Returns:

the computed statistic or Utils.missingValue() if the statistic can't be computed for some reason

toSummaryString

public String toSummaryString()

Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.

Returns:

a formatted string containing all the computed statistics

statisticIsMaximisable

public boolean statisticIsMaximisable(String statName)

True if the optimum value of the named metric is a maximum value; false if the optimim value is a minimum value. Subclasses should override this method to suit their statistic(s)

Overrides:

statisticIsMaximisable in class weka.classifiers.evaluation.AbstractEvaluationMetric

Returns:

true (default implementation)