Calculates the final prediction by performing the result of the
predictions of different metrics obtained through a SimpleVoting
class.
D2MCS::VotingStrategy -> CombinedVoting
new()Method for initializing the object arguments during runtime.
CombinedVoting$new(voting.schemes, combined.metrics, methodology, metrics)voting.schemesA list of elements inherited from
SimpleVoting.
combined.metricsAn object defining the metrics used to combine
the voting schemes. The object must inherit from
CombinedMetrics class.
methodologyAn object specifying the methodology used to execute
the combined voting. Object inherited from Methodology
object
metricsA character vector with the name of the metrics used to perform the combined voting operations. Metrics should be previously defined during training stage.
getCombinedMetrics()The function returns the metrics used to combine the metrics results.
CombinedVoting$getCombinedMetrics()An object inherited from CombinedMetrics class.
getMethodology()The function gets the methodology used to execute the combined votings.
CombinedVoting$getMethodology()An object inherited from Methodology class.
getFinalPred()The function returns the predictions obtained after executing the combined-voting methodology.
CombinedVoting$getFinalPred(type = NULL, target = NULL, filter = NULL)typeA character to define which type of predictions should be returned. If not defined all type of probabilities will be returned. Conversely if "prob" or "raw" is defined then computed 'probabilistic' or 'class' values are returned.
targetA character defining the value of the positive class.
filterA logical value used to specify if only predictions matching the target value should be returned or not. If TRUE the function returns only the predictions matching the target value. Conversely if FALSE (by default) the function returns all the predictions.
A data.frame with the computed predictions.
execute()The function implements the combined voting scheme.
CombinedVoting$execute(predictions, verbose = FALSE)predictionsA ClusterPredictions object containing
the predictions computed for each cluster.
verboseA logical value to specify if more verbosity is needed.
clone()The objects of this class are cloneable with this method.
CombinedVoting$clone(deep = FALSE)deepWhether to make a deep clone.
D2MCS, ClassMajorityVoting,
ClassWeightedVoting, ProbAverageVoting,
ProbAverageWeightedVoting, ProbBasedMethodology,
SimpleVoting