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/******************************************************************************
 *                   Confidential Proprietary                                 *
 *         (c) Copyright Haifeng Li 2011, All Rights Reserved                 *
 ******************************************************************************/

package smile.math.kernel;

import smile.math.SparseArray;
import smile.math.Math;

/**
 * The Gaussian Mercer Kernel. k(u, v) = e-||u-v||2 / (2 * σ2),
 * where σ > 0 is the scale parameter of the kernel.
 * 

* The Gaussian kernel is a good choice for a great deal of applications, * although sometimes it is remarked as being over used. * @author Haifeng Li */ public class SparseGaussianKernel implements MercerKernel { /** * The width of the kernel. */ private double gamma; /** * Constructor. * @param sigma the smooth/width parameter of Gaussian kernel. */ public SparseGaussianKernel(double sigma) { if (sigma <= 0) throw new IllegalArgumentException("sigma is not positive."); this.gamma = 0.5 / (sigma * sigma); } @Override public String toString() { return String.format("Sparse Gaussian Kernel (\u02E0 = %.4f)", Math.sqrt(0.5/gamma)); } @Override public double k(SparseArray x, SparseArray y) { return Math.exp(-gamma * Math.squaredDistance(x, y)); } }





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