smile.math.kernel.BinarySparseGaussianKernel Maven / Gradle / Ivy
/******************************************************************************
* Confidential Proprietary *
* (c) Copyright Haifeng Li 2011, All Rights Reserved *
******************************************************************************/
package smile.math.kernel;
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 kernel works
* on sparse binary array as int[], which are the indices of nonzero elements.
*
* The Gaussian kernel is a good choice for a great deal of applications,
* although sometimes it is remarked as being overused.
* @author Haifeng Li
*/
public class BinarySparseGaussianKernel implements MercerKernel {
/**
* The width of the kernel.
*/
private double gamma;
/**
* Constructor.
* @param sigma the smooth/width parameter of Gaussian kernel.
*/
public BinarySparseGaussianKernel(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 Binary Gaussian Kernel (\u02E0 = %.4f)", Math.sqrt(0.5/gamma));
}
@Override
public double k(int[] x, int[] y) {
double d = 0.0;
int p1 = 0, p2 = 0;
while (p1 < x.length && p2 < y.length) {
int i1 = x[p1];
int i2 = y[p2];
if (i1 == i2) {
p1++;
p2++;
} else if (i1 > i2) {
d++;
p2++;
} else {
d++;
p1++;
}
}
d += x.length - p1;
d += y.length - p2;
return Math.exp(-gamma * d);
}
}