/**
* Copyright (c) 2009/09-2012/08, Regents of the University of Colorado
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice, this
* list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
* ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* Copyright 2012/09-2013/04, 2013/11-Present, University of Massachusetts Amherst
* Copyright 2013/05-2013/10, IPSoft Inc.
*
* 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 com.clearnlp.classification.algorithm.old;
import java.util.List;
import org.apache.log4j.Logger;
import com.clearnlp.classification.prediction.StringPrediction;
import com.clearnlp.util.UTMath;
/**
* Abstract algorithm.
* @since 1.0.0
* @author Jinho D. Choi ({@code jdchoi77@gmail.com})
*/
abstract public class AbstractAlgorithm
{
protected final Logger LOG = Logger.getLogger(this.getClass());
/** The flag to indicate L2-regularized L1-loss support vector classification (dual). */
static public final byte SOLVER_LIBLINEAR_LR2_L1_SVC = 0;
/** The flag to indicate L2-regularized L2-loss support vector classification (dual). */
static public final byte SOLVER_LIBLINEAR_LR2_L2_SVC = 1;
/** The flag to indicate L2-regularized logistic regression (dual). */
static public final byte SOLVER_LIBLINEAR_LR2_LR = 2;
/** The flag to indicate adaptive gradient method using hinge loss. */
static public final byte SOLVER_ADAGRAD_HINGE = 3;
/** The flag to indicate adaptive gradient method using logistic regression. */
static public final byte SOLVER_ADAGRAD_LR = 4;
protected double[] getQD(List<int[]> xs, List<double[]> vs, double init, double bias)
{
int i, size = xs.size();
double[] qd = new double[size];
for (i=0; i<size; i++)
{
qd[i] = init + UTMath.sq(bias);
qd[i] += (vs != null) ? UTMath.squareSum(vs.get(i)) : xs.get(i).length;
}
return qd;
}
protected void normalize(double[] scores)
{
int i, size = scores.length;
double d, sum = 0;
for (i=0; i<size; i++)
{
d = Math.exp(scores[i]);
scores[i] = d;
sum += d;
}
for (i=0; i<size; i++)
scores[i] /= sum;
}
static public void normalize(List<StringPrediction> ps)
{
int i, size = ps.size();
StringPrediction p;
double d, sum = 0;
for (i=0; i<size; i++)
{
p = ps.get(i);
d = Math.exp(p.score);
p.score = d;
sum += d;
}
for (i=0; i<size; i++)
ps.get(i).score /= sum;
}
}