Example usage for weka.core Optimization findArgmin

Introduction

In this page you can find the example usage for weka.core Optimization findArgmin.

Prototype

public double[] findArgmin(double[] initX, double[][] constraints) throws Exception 

Source Link

Document

Main algorithm.

Usage

From source file:br.com.ufu.lsi.rebfnetwork.RBFModel.java

License:Open Source License

/**
 * Builds the RBF network regressor based on the given dataset.
 *///from   w  ww  . ja va2s .c  o m
public void buildClassifier(Instances data) throws Exception {

    // Set up the initial arrays
    m_data = initializeClassifier(data);

    if (m_ZeroR != null) {
        return;
    }

    // Initialise thread pool
    m_Pool = Executors.newFixedThreadPool(m_poolSize);

    // Apply optimization class to train the network
    Optimization opt = null;
    if (!m_useCGD) {
        opt = new OptEng();
    } else {
        opt = new OptEngCGD();
    }
    opt.setDebug(m_Debug);

    // No constraints
    double[][] b = new double[2][m_RBFParameters.length];
    for (int i = 0; i < 2; i++) {
        for (int j = 0; j < m_RBFParameters.length; j++) {
            b[i][j] = Double.NaN;
        }
    }

    m_RBFParameters = opt.findArgmin(m_RBFParameters, b);
    while (m_RBFParameters == null) {
        m_RBFParameters = opt.getVarbValues();
        if (m_Debug) {
            System.out.println("200 iterations finished, not enough!");
        }
        m_RBFParameters = opt.findArgmin(m_RBFParameters, b);
    }
    if (m_Debug) {
        System.out.println("SE (normalized space) after optimization: " + opt.getMinFunction());
    }

    m_data = new Instances(m_data, 0); // Save memory

    // Shut down thread pool
    m_Pool.shutdown();
}

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