it.uniroma2.sag.kelp.kernel.standard.RbfKernel.java Source code

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Here is the source code for it.uniroma2.sag.kelp.kernel.standard.RbfKernel.java

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/*
 * Copyright 2014 Simone Filice and Giuseppe Castellucci and Danilo Croce and Roberto Basili
 * 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 it.uniroma2.sag.kelp.kernel.standard;

import it.uniroma2.sag.kelp.data.example.Example;
import it.uniroma2.sag.kelp.kernel.Kernel;
import it.uniroma2.sag.kelp.kernel.KernelComposition;

import com.fasterxml.jackson.annotation.JsonTypeName;

/**
 * Radial Basis Function Kernel. <br>
 * Given a kernel K, the RBF formula Kr is: <br>
 * \(Kr(x,y) = e^{-\gamma * \left \lVert x-y \right \rVert ^2}\) where: <br>
 * \(\left\lVert a \right\rVert\) is the norm of a in the kernel space K, thus \(\left\lVert x-y \right\rVert ^2\) can be computed
 * as: <br>
 * \(\left\lVert x-y \right\rVert ^2 = \left\lVert x \right\rVert ^2 + \left\lVert y \right\rVert ^2 - 2K(x,y) = K(x,x) + K(y,y) - 2K(x,y)\)
 * 
 * @author Simone Filice
 */
@JsonTypeName("rbf")
public class RbfKernel extends KernelComposition {

    private float gamma;

    public RbfKernel(float gamma, Kernel inputSpace) {
        this.baseKernel = inputSpace;
        this.gamma = gamma;
    }

    public RbfKernel() {

    }

    /**
     * @return the gamma
     */
    public float getGamma() {
        return gamma;
    }

    /**
     * @param gamma
     *            the gamma to set
     */
    public void setGamma(float gamma) {
        this.gamma = gamma;
    }

    @Override
    protected float kernelComputation(Example exA, Example exB) {
        float innerProductOfTheDiff = this.baseKernel.squaredNormOfTheDifference(exA, exB);
        return (float) Math.exp(-gamma * innerProductOfTheDiff);
    }
}