Abstract class used as a template to define new customized strategies to combine the probability predictions made by different metrics.
new()
Method for initializing the object arguments during runtime.
Methodology$new(required.metrics)
required.metrics
A character vector of length greater than 2 with the name of the required metrics.
getRequiredMetrics()
The function returns the required metrics that will participate in the methodology to compute a metric based on all of them.
Methodology$getRequiredMetrics()
A character vector of length greater than 2 with the name of the required metrics.
compute()
Function to compute the probability of the final prediction based on different metrics.
Methodology$compute(raw.pred, prob.pred, positive.class, negative.class)
raw.pred
A character list of length greater than 2 with the class value of the predictions made by the metrics.
prob.pred
A numeric list of length greater than 2 with the probability of the predictions made by the metrics.
positive.class
A character with the value of the positive class.
negative.class
A character with the value of the negative class.
A numeric value indicating the probability of the instance is predicted as positive class.
clone()
The objects of this class are cloneable with this method.
Methodology$clone(deep = FALSE)
deep
Whether to make a deep clone.
ProbBasedMethodology