c

undersampling.core

EasyEnsemble

class EasyEnsemble extends Algorithm

Easy Ensemble algorithm. Original paper: "Exploratory Undersampling for Class-Imbalance Learning" by Xu-Ying Liu, Jianxin Wu and Zhi-Hua Zhou.

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Instance Constructors

  1. new EasyEnsemble(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, ratio: Double = 1.0, replacement: Boolean = false, nTimes: Int = 5): Data

    Compute the Easy Ensemble algorithm.

    Compute the Easy Ensemble algorithm.

    file

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

    ratio

    ratio to know how many majority class examples to preserve. By default it's set to 1 so there will be the same minority class examples as majority class examples. It will take numMinorityInstances * ratio

    replacement

    whether or not to sample randomly with replacement or not. false by default

    nTimes

    times to perform the random undersampling

    returns

    Data structure with all the important information and index of elements kept

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  1. def finalize(): Unit
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    Deprecated

    (Since version ) see corresponding Javadoc for more information.

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