MinimizeFP | R Documentation |
Calculates if the positive class is the predicted one in all metrics, otherwise, the instance is not considered to have the positive class associated.
D2MCS::CombinedMetrics
-> MinimizeFP
new()
Method for initializing the object arguments during runtime.
MinimizeFP$new(required.metrics = c("MCC", "PPV"))
required.metrics
A character vector of length greater than 2 with the name of the required metrics.
getFinalPrediction()
Function to obtain the final prediction based on different metrics.
MinimizeFP$getFinalPrediction( 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 logical value indicating if the instance is predicted as positive class or not.
clone()
The objects of this class are cloneable with this method.
MinimizeFP$clone(deep = FALSE)
deep
Whether to make a deep clone.
CombinedMetrics
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