PPV: Computes the Positive Predictive Value.

In D2MCS: Data Driving Multiple Classifier System

Computes the Positive Predictive Value.

Description

Positive Predictive Values are the proportions of positive results in statistics and diagnostic tests that are true positive results.

Details

PPV = TP / (TP + FP)

Super class

D2MCS::MeasureFunction -> PPV

Methods

Public methods

• PPV$new()

• PPV$compute()

• PPV$clone()

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Method new()

Method for initializing the object arguments during runtime.

Usage

PPV$new(performance.output = NULL)

Arguments

performance.output

An optional ConfMatrix parameter to define the type of object used as basis to compute the PPV measure.

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Method compute()

The function computes the PPV achieved by the M.L. model.

Usage

PPV$compute(performance.output = NULL)

Arguments

performance.output

An optional ConfMatrix parameter to define the type of object used as basis to compute the PPV measure.

Details

This function is automatically invoke by the ClassificationOutput object.

Returns

A numeric vector of size 1 or NULL if an error occurred.

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Method clone()

The objects of this class are cloneable with this method.

Usage

PPV$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

MeasureFunction, ClassificationOutput, ConfMatrix

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