ProbBasedMethodology: Methodology to obtain the combination of the probability of...

In D2MCS: Data Driving Multiple Classifier System

Methodology to obtain the combination of the probability of different metrics.

Description

Calculates the mean of the probabilities of the different metrics.

Super class

D2MCS::Methodology -> ProbBasedMethodology

Methods

Public methods

• ProbBasedMethodology$new()

• ProbBasedMethodology$compute()

• ProbBasedMethodology$clone()

Inherited methods

• D2MCS::Methodology$getRequiredMetrics()

---

Method new()

Method for initializing the object arguments during runtime.

Usage

ProbBasedMethodology$new(required.metrics = c("MCC", "PPV"))

Arguments

required.metrics

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

---

Method compute()

Function to compute the probability of the final prediction based on different metrics.

Usage

ProbBasedMethodology$compute(
  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 numeric value indicating the probability of the instance is predicted as positive class.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

ProbBasedMethodology$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Methodology

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