/* * Apache License * Version 2.0, January 2004 * http://www.apache.org/licenses/ * * Copyright 2013 Aurelian Tutuianu * Copyright 2014 Aurelian Tutuianu * Copyright 2015 Aurelian Tutuianu * Copyright 2016 Aurelian Tutuianu * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * */ package rapaio.ml.classifier.svm.kernel; import rapaio.data.Frame; import rapaio.sys.WS; /** * Spherical Kernel * <p> * The spherical kernel is similar to the circular kernel, but is positive definite in R3. * <p> * k(x, y) = 1 - \frac{3}{2} \frac{\lVert x-y \rVert}{\sigma} + \frac{1}{2} \left( \frac{ \lVert x-y \rVert}{\sigma} \right)^3 * <p> * \mbox{if}~ \lVert x-y \rVert < \sigma \mbox{, zero otherwise} * <p> * Created by <a href="mailto:padreati@yahoo.com">Aurelian Tutuianu</a> at 1/19/15. */ public class SphericalKernel extends AbstractKernel { private static final long serialVersionUID = -7447828392149152605L; private final double sigma; public SphericalKernel(double sigma) { this.sigma = sigma; } @Override public double eval(Frame df1, int row1, Frame df2, int row2) { double dot = deltaDotProd(df1, row1, df2, row2); if (dot < sigma) return 0; double f = dot / sigma; return 1 - 3 * f / 2 + Math.pow(f, 3) / 2; } @Override public Kernel newInstance() { return new SphericalKernel(sigma); } @Override public String name() { return "Spherical(sigma=" + WS.formatFlex(sigma) + ")"; } }