NoProbability: Compute performance across resamples.

In D2MCS: Data Driving Multiple Classifier System

Compute performance across resamples.

Description

Computes the performance across resamples when class probabilities cannot be computed.

Super class

D2MCS::SummaryFunction -> NoProbability

Methods

Public methods

• NoProbability$new()

• NoProbability$execute()

• NoProbability$clone()

Inherited methods

• D2MCS::SummaryFunction$getMeasures()

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Method new()

The function defined during runtime the usage of five measures: 'Kappa', 'Accuracy', 'TCR_9', 'MCC' and 'PPV'.

Usage

NoProbability$new()

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Method execute()

The function computes the performance across resamples using the previously defined measures.

Usage

NoProbability$execute(data, lev = NULL, model = NULL)

Arguments

data

A data.frame containing the data used to compute the performance.

lev

An optional value used to define the levels of the target class.

model

An optional value used to define the M.L. model used.

Returns

A vector of performance estimates.

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Method clone()

The objects of this class are cloneable with this method.

Usage

NoProbability$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

SummaryFunction

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