Example usage for weka.core.matrix Matrix solve

Introduction

In this page you can find the example usage for weka.core.matrix Matrix solve.

Prototype

public Matrix solve(Matrix B) 

Source Link

Document

Solve A*X = B

Usage

From source file:mulan.classifier.neural.ThresholdFunction.java

License:Open Source License

/**
 * Build a threshold function for based on input data.
 * The threshold function is build for a particular model.
 *
 * @param idealLabels the ideal output for each input patterns, which a model should output.
 *                  First index is expected to be number of examples and second is the label index.
 * @param modelOutLabels the real output of a model for each input pattern.
 *                    First index is expected to be number of examples and second is the label index.
 * @throws IllegalArgumentException if dimensions of input arrays does not match
 */// ww w. j a  v a2  s  .c o  m
public void build(final double[][] idealLabels, final double[][] modelOutLabels) {

    if (idealLabels == null || modelOutLabels == null) {
        throw new IllegalArgumentException("Non of the input parameters can be null.");
    }

    int numExamples = idealLabels.length;
    int numLabels = idealLabels[0].length;

    if (modelOutLabels.length != numExamples || modelOutLabels[0].length != numLabels) {
        throw new IllegalArgumentException("Matrix dimensions of input parameters does not agree.");
    }

    double[] thresholds = new double[numExamples];
    double[] isLabelModelOuts = new double[numLabels];
    double[] isNotLabelModelOuts = new double[numLabels];
    for (int example = 0; example < numExamples; example++) {
        Arrays.fill(isLabelModelOuts, Double.MAX_VALUE);
        Arrays.fill(isNotLabelModelOuts, -Double.MAX_VALUE);
        for (int label = 0; label < numLabels; label++) {
            if (idealLabels[example][label] == 1) {
                isLabelModelOuts[label] = modelOutLabels[example][label];
            } else {
                isNotLabelModelOuts[label] = modelOutLabels[example][label];
            }
        }
        double isLabelMin = isLabelModelOuts[Utils.minIndex(isLabelModelOuts)];
        double isNotLabelMax = isNotLabelModelOuts[Utils.maxIndex(isNotLabelModelOuts)];

        // check if we have unique minimum ...
        // if not take center of the segment ... if it is a segment
        if (isLabelMin != isNotLabelMax) {
            // check marginal cases -> all labels are in or none of them
            if (isLabelMin == Double.MAX_VALUE) {
                thresholds[example] = isNotLabelMax + 0.1;
            } else if (isNotLabelMax == -Double.MAX_VALUE) {
                thresholds[example] = isLabelMin - 0.1;
            } else {
                // center of a segment
                thresholds[example] = (isLabelMin + isNotLabelMax) / 2;
            }
        } else {
            // when minimum is unique
            thresholds[example] = isLabelMin;
        }
    }

    Matrix modelMatrix = new Matrix(numExamples, numLabels + 1, 1.0);
    modelMatrix.setMatrix(0, numExamples - 1, 0, numLabels - 1, new Matrix(modelOutLabels));
    Matrix weights = modelMatrix.solve(new Matrix(thresholds, thresholds.length));
    double[][] weightsArray = weights.transpose().getArray();

    parameters = Arrays.copyOf(weightsArray[0], weightsArray[0].length);
}

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