CombinedVoting: Implementation of Combined Voting.

In D2MCS: Data Driving Multiple Classifier System

Implementation of Combined Voting.

Description

Calculates the final prediction by performing the result of the predictions of different metrics obtained through a SimpleVoting class.

Super class

D2MCS::VotingStrategy -> CombinedVoting

Methods

Public methods

• CombinedVoting$new()

• CombinedVoting$getCombinedMetrics()

• CombinedVoting$getMethodology()

• CombinedVoting$getFinalPred()

• CombinedVoting$execute()

• CombinedVoting$clone()

Inherited methods

• D2MCS::VotingStrategy$getMetrics()
• D2MCS::VotingStrategy$getName()
• D2MCS::VotingStrategy$getVotingSchemes()

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Method new()

Method for initializing the object arguments during runtime.

Usage

CombinedVoting$new(voting.schemes, combined.metrics, methodology, metrics)

Arguments

voting.schemes

A list of elements inherited from SimpleVoting.

combined.metrics

An object defining the metrics used to combine the voting schemes. The object must inherit from CombinedMetrics class.

methodology

An object specifying the methodology used to execute the combined voting. Object inherited from Methodology object

metrics

A character vector with the name of the metrics used to perform the combined voting operations. Metrics should be previously defined during training stage.

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Method getCombinedMetrics()

The function returns the metrics used to combine the metrics results.

Usage

CombinedVoting$getCombinedMetrics()

Returns

An object inherited from CombinedMetrics class.

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Method getMethodology()

The function gets the methodology used to execute the combined votings.

Usage

CombinedVoting$getMethodology()

Returns

An object inherited from Methodology class.

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Method getFinalPred()

The function returns the predictions obtained after executing the combined-voting methodology.

Usage

CombinedVoting$getFinalPred(type = NULL, target = NULL, filter = NULL)

Arguments

type

A character to define which type of predictions should be returned. If not defined all type of probabilities will be returned. Conversely if "prob" or "raw" is defined then computed 'probabilistic' or 'class' values are returned.

target

A character defining the value of the positive class.

filter

A logical value used to specify if only predictions matching the target value should be returned or not. If TRUE the function returns only the predictions matching the target value. Conversely if FALSE (by default) the function returns all the predictions.

Returns

A data.frame with the computed predictions.

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Method execute()

The function implements the combined voting scheme.

Usage

CombinedVoting$execute(predictions, verbose = FALSE)

Arguments

predictions

A ClusterPredictions object containing the predictions computed for each cluster.

verbose

A logical value to specify if more verbosity is needed.

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Method clone()

The objects of this class are cloneable with this method.

Usage

CombinedVoting$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

D2MCS, ClassMajorityVoting, ClassWeightedVoting, ProbAverageVoting, ProbAverageWeightedVoting, ProbBasedMethodology, SimpleVoting

D2MCS documentation built on Aug. 23, 2022, 5:07 p.m.