org.nd4j.linalg.dataset.api.preprocessor.classimbalance.UnderSamplingByMaskingPreProcessor Maven / Gradle / Ivy
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* * This program and the accompanying materials are made available under the
* * terms of the Apache License, Version 2.0 which is available at
* * https://www.apache.org/licenses/LICENSE-2.0.
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* * SPDX-License-Identifier: Apache-2.0
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package org.nd4j.linalg.dataset.api.preprocessor.classimbalance;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.dataset.api.DataSet;
import org.nd4j.linalg.dataset.api.DataSetPreProcessor;
public class UnderSamplingByMaskingPreProcessor extends BaseUnderSamplingPreProcessor implements DataSetPreProcessor {
private double targetMinorityDist;
private int minorityLabel = 1;
/**
* The target distribution to approximate. Valid values are between (0,0.5].
* Eg. For a targetDist = 0.25 and tbpttWindowSize = 100:
* Every 100 time steps (starting from the last time step) will randomly mask majority time steps to approximate a 25:75 ratio of minorityLabel to majority classes
* @param targetDist
* @param windowSize Usually set to the size of the tbptt
*/
public UnderSamplingByMaskingPreProcessor(double targetDist, int windowSize) {
if (targetDist > 0.5 || targetDist <= 0) {
throw new IllegalArgumentException(
"Target distribution for the minorityLabel class has to be greater than 0 and no greater than 0.5. Target distribution of "
+ targetDist + "given");
}
this.targetMinorityDist = targetDist;
this.tbpttWindowSize = windowSize;
}
/**
* Will change the default minority label from "1" to "0" and correspondingly the majority class from "0" to "1"
*/
public void overrideMinorityDefault() {
this.minorityLabel = 0;
}
@Override
public void preProcess(DataSet toPreProcess) {
INDArray label = toPreProcess.getLabels();
INDArray labelMask = toPreProcess.getLabelsMaskArray();
INDArray sampledMask = adjustMasks(label, labelMask, minorityLabel, targetMinorityDist);
toPreProcess.setLabelsMaskArray(sampledMask);
}
}