| Methodology {D2MCS} | R Documentation |
Abstract class to compute the probability prediction based on combination between metrics.
Description
Abstract class used as a template to define new customized strategies to combine the probability predictions made by different metrics.
Methods
Public methods
Method new()
Method for initializing the object arguments during runtime.
Usage
Methodology$new(required.metrics)
Arguments
required.metricsA character vector of length greater than 2 with the name of the required metrics.
Method getRequiredMetrics()
The function returns the required metrics that will participate in the methodology to compute a metric based on all of them.
Usage
Methodology$getRequiredMetrics()
Returns
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
Methodology$compute(raw.pred, prob.pred, positive.class, negative.class)
Arguments
raw.predA character list of length greater than 2 with the class value of the predictions made by the metrics.
prob.predA numeric list of length greater than 2 with the probability of the predictions made by the metrics.
positive.classA character with the value of the positive class.
negative.classA character with the value of the negative class.
Returns
A numeric value indicating the probability of the instance is predicted as positive class.
Method clone()
The objects of this class are cloneable with this method.
Usage
Methodology$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.