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Scalable machine learning libraries

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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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 org.apache.mahout.classifier.sgd;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;

/**
 * Implements the Gaussian prior.  This prior has a tendency to decrease large coefficients toward zero, but
 * doesn't tend to set them to exactly zero.
 */
public class L2 implements PriorFunction {

  private static final double HALF_LOG_2PI = Math.log(2.0 * Math.PI) / 2.0;

  private double s2;
  private double s;

  public L2(double scale) {
    s = scale;
    s2 = scale * scale;
  }

  public L2() {
    s = 1.0;
    s2 = 1.0;
  }

  @Override
  public double age(double oldValue, double generations, double learningRate) {
    return oldValue * Math.pow(1.0 - learningRate / s2, generations);
  }

  @Override
  public double logP(double betaIJ) {
    return -betaIJ * betaIJ / s2 / 2.0 - Math.log(s) - HALF_LOG_2PI;
  }

  @Override
  public void write(DataOutput out) throws IOException {
    out.writeDouble(s2);
    out.writeDouble(s);
  }

  @Override
  public void readFields(DataInput in) throws IOException {
    s2 = in.readDouble();
    s = in.readDouble();
  }
}