/**
* This file is part of FNLP (formerly FudanNLP).
*
* FNLP is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* FNLP is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with FudanNLP. If not, see <http://www.gnu.org/licenses/>.
*
* Copyright 2009-2014 www.fnlp.org. All rights reserved.
*/
package org.fnlp.demo.ml;
import java.io.File;
import org.fnlp.data.reader.SimpleFileReader;
import org.fnlp.ml.classifier.linear.Linear;
import org.fnlp.ml.classifier.linear.OnlineTrainer;
import org.fnlp.ml.classifier.linear.inf.Inferencer;
import org.fnlp.ml.classifier.linear.inf.LinearMax;
import org.fnlp.ml.classifier.linear.update.LinearMaxPAUpdate;
import org.fnlp.ml.feature.Generator;
import org.fnlp.ml.feature.SFGenerator;
import org.fnlp.ml.loss.ZeroOneLoss;
import org.fnlp.ml.types.InstanceSet;
import org.fnlp.ml.types.alphabet.AlphabetFactory;
import org.fnlp.ml.types.alphabet.IFeatureAlphabet;
import org.fnlp.ml.types.alphabet.LabelAlphabet;
import org.fnlp.nlp.pipe.StringArray2IndexArray;
import org.fnlp.nlp.pipe.Pipe;
import org.fnlp.nlp.pipe.SeriesPipes;
import org.fnlp.nlp.pipe.Target2Label;
/**
* 线性分类器使用示例
*
* @author xpqiu
*
*/
public class SimpleClassifier2 {
static InstanceSet train;
static InstanceSet test;
static AlphabetFactory factory = AlphabetFactory.buildFactory();
static LabelAlphabet al = factory.DefaultLabelAlphabet();
static IFeatureAlphabet af = factory.DefaultFeatureAlphabet();
static String path = null;
public static void main(String[] args) throws Exception {
long start = System.currentTimeMillis();
path = "./example-data/data-classification.txt";
Pipe lpipe = new Target2Label(al);
Pipe fpipe = new StringArray2IndexArray(factory, true);
//构造转换器组
Pipe pipe = new SeriesPipes(new Pipe[]{lpipe,fpipe});
//构建训练集
train = new InstanceSet(pipe, factory);
SimpleFileReader reader = new SimpleFileReader (path,true);
train.loadThruStagePipes(reader);
al.setStopIncrement(true);
//构建测试集
test = new InstanceSet(pipe, factory);
reader = new SimpleFileReader (path,true);
test.loadThruStagePipes(reader);
System.out.println("Train Number: " + train.size());
System.out.println("Test Number: " + test.size());
System.out.println("Class Number: " + al.size());
float c = 1.0f;
int round = 20;
Generator featureGen = new SFGenerator();
ZeroOneLoss loss = new ZeroOneLoss();
LinearMaxPAUpdate update = new LinearMaxPAUpdate(loss);
Inferencer msolver = new LinearMax(featureGen, al.size() );
OnlineTrainer trainer = new OnlineTrainer(msolver, update, loss, af.size(), round,
c);
Linear classify = trainer.train(train, test);
String modelFile = path+".m.gz";
classify.saveTo(modelFile);
long end = System.currentTimeMillis();
System.out.println("Total Time: " + (end - start));
System.out.println("End!");
(new File(modelFile)).deleteOnExit();
System.exit(0);
}
}