org.nd4j.linalg.dataset.api.preprocessor.classimbalance.UnderSamplingByMaskingPreProcessor Maven / Gradle / Ivy
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;
/**
* For use in time series with unbalanced binary classes trained with truncated back prop through time
* Undersamples the majority class by randomly masking time steps belonging to it
* Given a target distribution for the minority class and the window size (usually the value used with tbptt)
* the preprocessor will approximate the given target distribution for every window of given size for every sample of the minibatch
* By default '0' is considered the majority class and '1' the minorityLabel class
* Default can be overriden with .overrideMinorityDefault()
*
* ONLY masks belonging to the majority class are modified
* If a tbptt segment contains only majority class labels all time steps in that segment are masked. Can be overriden with
* donotMaskMinorityWindows() in which case 1 - target distribution % of time steps are masked
* @author susaneraly
*/
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);
}
}