Sensitivity: Computes the Sensitivity Value.

In D2MCS: Data Driving Multiple Classifier System

Computes the Sensitivity Value.

Description

Sensitivity is a measure of the proportion of actual positive cases that got predicted as positive (or true positive).

Details

Sensitivity = TP / (TP + FN)

Super class

D2MCS::MeasureFunction -> Sensitivity

Methods

Public methods

• Sensitivity$new()

• Sensitivity$compute()

• Sensitivity$clone()

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Method new()

Method for initializing the object arguments during runtime.

Usage

Sensitivity$new(performance.output = NULL)

Arguments

performance.output

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

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Method compute()

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

Usage

Sensitivity$compute(performance.output = NULL)

Arguments

performance.output

An optional ConfMatrix parameter to define the type of object used as basis to compute the Sensitivity 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

Sensitivity$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.