CombinedMetrics: Abstract class to compute the class prediction based on...

In D2MCS: Data Driving Multiple Classifier System

Abstract class to compute the class prediction based on combination between metrics.

Description

Abstract class used as a template to define new customized strategies to combine the class predictions made by different metrics.

Methods

Public methods

• CombinedMetrics$new()

• CombinedMetrics$getRequiredMetrics()

• CombinedMetrics$getFinalPrediction()

• CombinedMetrics$clone()

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Method new()

Method for initializing the object arguments during runtime.

Usage

CombinedMetrics$new(required.metrics)

Arguments

required.metrics

A character vector of length greater than 2 with the name of the required metrics.

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Method getRequiredMetrics()

The function returns the required metrics that will participate in the combined metric process.

Usage

CombinedMetrics$getRequiredMetrics()

Returns

A character vector of length greater than 2 with the name of the required metrics.

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Method getFinalPrediction()

Function used to implement the strategy to obtain the final prediction based on different metrics.

Usage

CombinedMetrics$getFinalPrediction(
  raw.pred,
  prob.pred,
  positive.class,
  negative.class
)

Arguments

raw.pred

A character list of length greater than 2 with the class value of the predictions made by the metrics.

prob.pred

A numeric list of length greater than 2 with the probability of the predictions made by the metrics.

positive.class

A character with the value of the positive class.

negative.class

A character with the value of the negative class.

Returns

A logical value indicating if the instance is predicted as positive class or not.

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Method clone()

The objects of this class are cloneable with this method.

Usage

CombinedMetrics$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

CombinedVoting

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