MCCHeuristic: Feature-clustering based on Matthews Correlation Coefficient...

In D2MCS: Data Driving Multiple Classifier System

Feature-clustering based on Matthews Correlation Coefficient score.

Description

Performs the feature-clustering using MCC score. Valid for both bi-class and multi-class problems

Super class

D2MCS::GenericHeuristic -> MCCHeuristic

Methods

Public methods

• MCCHeuristic$new()

• MCCHeuristic$heuristic()

• MCCHeuristic$clone()

---

Method new()

Empty function used to initialize the object arguments in runtime.

Usage

MCCHeuristic$new()

---

Method heuristic()

Calculates the Matthews correlation Coefficient (MCC) score.

Usage

MCCHeuristic$heuristic(col1, col2, column.names = NULL)

Arguments

col1

A numeric vector or matrix required to perform the clustering operation.

col2

A numeric vector or matrix to perform the clustering operation.

column.names

An optional character vector with the names of both columns.

Returns

A numeric vector of length 1 or NA if an error occurs.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

MCCHeuristic$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Dataset, mccr

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