c

undersampling.core

EvolutionaryUnderSampling

class EvolutionaryUnderSampling extends Algorithm

Evolutionary Under Sampling. Original paper: "Evolutionary Under-Sampling for Classification with Imbalanced Data Sets: Proposals and Taxonomy" by Salvador Garcia and Francisco Herrera.

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Instance Constructors

  1. new EvolutionaryUnderSampling(data: Data, seed: Long = System.currentTimeMillis(), minorityClass: Any = -1)

    data

    data to work with

    seed

    seed to use. If it is not provided, it will use the system time

    minorityClass

    indicates the minority class. If it's set to -1, it will set to the one with less instances

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  14. def sample(file: Option[String] = None, populationSize: Int = 50, maxEvaluations: Int = 1000, algorithm: String = "EBUSMSGM", distance: Distance = Distances.EUCLIDEAN, probHUX: Double = 0.25, recombination: Double = 0.35, prob0to1: Double = 0.05): Data

    Compute Evolutionary Under Sampling

    Compute Evolutionary Under Sampling

    file

    file to store the log. If its set to None, log process would not be done

    populationSize

    number of chromosomes to generate

    maxEvaluations

    number of evaluations

    algorithm

    version of algorithm to execute. One of: EBUSGSGM, EBUSMSGM, EBUSGSAUC, EBUSMSAUC, EUSCMGSGM, EUSCMMSGM, EUSCMGSAUC or EUSCMMSAUC

    distance

    distance to use when calling the NNRule algorithm

    probHUX

    probability of changing a gen from 0 to 1 (used in crossover)

    recombination

    recombination threshold (used in reinitialization)

    prob0to1

    probability of changing a gen from 0 to 1 (used in reinitialization)

    returns

    Data structure with all the important information

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    Deprecated

    (Since version ) see corresponding Javadoc for more information.

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