Java tutorial
/* * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or GITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see <http://www.gnu.org/licenses/>. */ /* * Copyright (C) 2012 James Jesensky */ package jjj.asap.sas.models1.job; import java.io.FileNotFoundException; import java.util.Arrays; import java.util.HashMap; import java.util.LinkedList; import java.util.List; import java.util.Map; import java.util.Queue; import java.util.concurrent.Future; import jjj.asap.sas.util.Bucket; import jjj.asap.sas.util.Job; import jjj.asap.sas.util.Progress; import jjj.asap.sas.weka.ModelBuilder; import weka.attributeSelection.InfoGainAttributeEval; import weka.attributeSelection.Ranker; import weka.classifiers.AbstractClassifier; import weka.classifiers.Classifier; import weka.classifiers.bayes.BayesNet; import weka.classifiers.bayes.NaiveBayes; import weka.classifiers.bayes.net.estimate.BMAEstimator; import weka.classifiers.functions.RBFNetwork; import weka.classifiers.functions.SMO; import weka.classifiers.functions.supportVector.RBFKernel; import weka.classifiers.meta.AttributeSelectedClassifier; import weka.core.SelectedTag; /** * Builds a bucket of basic models */ public class BuildRBFKernelModels extends Job { /** * args[0] - input bucket * args[1] - output bucket */ public static void main(String[] args) throws Exception { Job job = new BuildRBFKernelModels(args[0], args[1]); Job.log("ARGS", Arrays.toString(args)); job.start(); } private String inputBucket; private String outputBucket; public BuildRBFKernelModels(String inputBucket, String outputBucket) { super(); this.inputBucket = inputBucket; this.outputBucket = outputBucket; } @Override protected void run() throws Exception { // validate args if (!Bucket.isBucket("datasets", inputBucket)) { throw new FileNotFoundException(inputBucket); } if (!Bucket.isBucket("models", outputBucket)) { throw new FileNotFoundException(outputBucket); } // init multi-threading Job.startService(); final Queue<Future<Object>> queue = new LinkedList<Future<Object>>(); // get the input from the bucket List<String> names = Bucket.getBucketItems("datasets", this.inputBucket); for (String dsn : names) { SMO smo = new SMO(); smo.setFilterType(new SelectedTag(SMO.FILTER_NONE, SMO.TAGS_FILTER)); smo.setBuildLogisticModels(true); RBFKernel kernel = new RBFKernel(); kernel.setGamma(0.05); smo.setKernel(kernel); AttributeSelectedClassifier asc = new AttributeSelectedClassifier(); asc.setEvaluator(new InfoGainAttributeEval()); Ranker ranker = new Ranker(); ranker.setThreshold(0.01); asc.setSearch(ranker); asc.setClassifier(smo); queue.add(Job.submit(new ModelBuilder(dsn, "InfoGain-SMO-RBFKernel", asc, this.outputBucket))); } // wait on complete Progress progress = new Progress(queue.size(), this.getClass().getSimpleName()); while (!queue.isEmpty()) { try { queue.remove().get(); } catch (Exception e) { Job.log("ERROR", e.toString()); } progress.tick(); } progress.done(); Job.stopService(); } }