Package adaa.analytics.rules.logic.representation.ruleset

Class SurvivalRuleSet

java.lang.Object

adaa.analytics.rules.logic.representation.ruleset.PredictionModel

adaa.analytics.rules.logic.representation.ruleset.RuleSetBase

adaa.analytics.rules.logic.representation.ruleset.SurvivalRuleSet

All Implemented Interfaces:

Serializable

public class SurvivalRuleSet
extends RuleSetBase

Class representing a set of survival rules.

See Also:

• Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class adaa.analytics.rules.logic.representation.ruleset.RuleSetBase

RuleSetBase.Significance

Field Summary

Fields

Modifier and Type	Field	Description
static final String	ANNOTATION_TRAINING_ESTIMATOR	Annotation representing survival function estimator of the training set (in a text form).
static final String	ANNOTATION_TRAINING_ESTIMATOR_REV	Annotation storing reveresed survival estimator of the training set (in a text form).
static final String	ATTRIBUTE_ESTIMATOR	Name of the prediction attribute representing survival function estimator (in a text form).
protected KaplanMeierEstimator	trainingEstimator	Training set estimator.

Fields inherited from class adaa.analytics.rules.logic.representation.ruleset.RuleSetBase

ANNOTATION_TEST_REPORT, attributes, growingTime, isVoting, knowledge, params, pruningTime, rules, totalTime

Constructor Summary

Constructors

Constructor	Description
SurvivalRuleSet(IExampleSet exampleSet, boolean isVoting, InductionParameters params, Knowledge knowledge)	Invokes base class constructor and calculates survival function estimator for the training set.

Method Summary

Modifier and Type	Method	Description
IExampleSet	apply(IExampleSet exampleSet)	Applies the rule model on a given set (estimates survival functions for all examples).
protected IAttribute	createPredictionAttributes(IExampleSet exampleSet, IAttribute label)	Computes prediction attributes (survival estimator) for a given set.
KaplanMeierEstimator	getTrainingEstimator()	Gets trainingEstimator}.
double	predict(Example example)	Estimates survival function for a given example and stores in a text form in ATTRIBUTE_ESTIMATOR attribute.
String	toString()	Generates text representation of the survival rule set.

Methods inherited from class adaa.analytics.rules.logic.representation.ruleset.RuleSetBase

addRule, calculateAvgRuleCoverage, calculateAvgRulePrecision, calculateAvgRuleQuality, calculateConditionsCount, calculateInducedCondtionsCount, calculateSignificance, calculateSignificanceFDR, calculateSignificanceFWER, getGrowingTime, getIsVoting, getParams, getPruningTime, getRules, getTotalTime, performPrediction, setGrowingTime, setIsVoting, setPruningTime, setTotalTime, toTable

Methods inherited from class adaa.analytics.rules.logic.representation.ruleset.PredictionModel

checkCompatibility, getLabel, getTrainingHeader, supportsConfidences

Methods inherited from class java.lang.Object

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

Field Details

ATTRIBUTE_ESTIMATOR

public static final String ATTRIBUTE_ESTIMATOR

Name of the prediction attribute representing survival function estimator (in a text form).

See Also:

• Constant Field Values

ANNOTATION_TRAINING_ESTIMATOR

public static final String ANNOTATION_TRAINING_ESTIMATOR

Annotation representing survival function estimator of the training set (in a text form).

See Also:

• Constant Field Values

ANNOTATION_TRAINING_ESTIMATOR_REV

public static final String ANNOTATION_TRAINING_ESTIMATOR_REV

Annotation storing reveresed survival estimator of the training set (in a text form).

See Also:

• Constant Field Values

trainingEstimator

protected KaplanMeierEstimator trainingEstimator

Training set estimator.

Constructor Details

SurvivalRuleSet

public SurvivalRuleSet(IExampleSet exampleSet,
 boolean isVoting,
 InductionParameters params,
 Knowledge knowledge)

Invokes base class constructor and calculates survival function estimator for the training set.

Parameters:

exampleSet - Training set.

isVoting - Voting flag.

params - Induction parameters.

knowledge - User's knowledge.

Method Details

getTrainingEstimator

public KaplanMeierEstimator getTrainingEstimator()

Gets trainingEstimator}.

predict

public double predict(Example example)

Estimates survival function for a given example and stores in a text form in ATTRIBUTE_ESTIMATOR attribute.

Specified by:

predict in class RuleSetBase

Parameters:

example - Example to be examined.

Returns:

Should be ignored (always 0).

apply

public IExampleSet apply(IExampleSet exampleSet)
                  throws OperatorException

Applies the rule model on a given set (estimates survival functions for all examples).

Overrides:

apply in class PredictionModel

Parameters:

exampleSet - Example set to be examined.

Returns:

Example set with filled estimates and annotations.

Throws:

OperatorException

createPredictionAttributes

protected IAttribute createPredictionAttributes(IExampleSet exampleSet,
 IAttribute label)

Computes prediction attributes (survival estimator) for a given set.

Overrides:

createPredictionAttributes in class PredictionModel

Parameters:

exampleSet - Example set to be examined.

label - Input label attribute.

Returns:

Output label attribute.

toString

public String toString()

Generates text representation of the survival rule set. Beside list of rules, it contains survival function estimates of the entire training set and particular rules.

Overrides:

toString in class RuleSetBase

Returns:

Rule set in the text form.