Java tutorial
/* * 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 com.ml.ira.algos; import com.google.common.collect.Lists; import com.google.common.io.Closeables; import org.apache.mahout.classifier.sgd.*; import org.apache.mahout.math.stats.GlobalOnlineAuc; import org.apache.mahout.math.stats.GroupedOnlineAuc; import org.apache.mahout.math.stats.OnlineAuc; import java.io.*; import java.util.HashMap; import java.util.List; import java.util.Locale; import java.util.Map; public class AdaptiveLogisticModelParameters extends LogisticModelParameters { private AdaptiveLogisticRegression alr; private int interval = 800; private int averageWindow = 500; private int threads = 4; private String prior = "L1"; private double priorOption = Double.NaN; private String auc = null; public AdaptiveLogisticRegression createAdaptiveLogisticRegression() { if (alr == null) { alr = new AdaptiveLogisticRegression(getMaxTargetCategories(), getNumFeatures(), createPrior(prior, priorOption)); alr.setInterval(interval); alr.setAveragingWindow(averageWindow); alr.setThreadCount(threads); alr.setAucEvaluator(createAUC(auc)); } return alr; } public void checkParameters() { if (prior != null) { String priorUppercase = prior.toUpperCase(Locale.ENGLISH).trim(); if (("TP".equals(priorUppercase) || "EBP".equals(priorUppercase)) && Double.isNaN(priorOption)) { throw new IllegalArgumentException( "You must specify a double value for TPrior and ElasticBandPrior."); } } } private static PriorFunction createPrior(String cmd, double priorOption) { if (cmd == null) { return null; } if ("L1".equals(cmd.toUpperCase(Locale.ENGLISH).trim())) { return new L1(); } if ("L2".equals(cmd.toUpperCase(Locale.ENGLISH).trim())) { return new L2(); } if ("UP".equals(cmd.toUpperCase(Locale.ENGLISH).trim())) { return new UniformPrior(); } if ("TP".equals(cmd.toUpperCase(Locale.ENGLISH).trim())) { return new TPrior(priorOption); } if ("EBP".equals(cmd.toUpperCase(Locale.ENGLISH).trim())) { return new ElasticBandPrior(priorOption); } return null; } private static OnlineAuc createAUC(String cmd) { if (cmd == null) { return null; } if ("GLOBAL".equals(cmd.toUpperCase(Locale.ENGLISH).trim())) { return new GlobalOnlineAuc(); } if ("GROUPED".equals(cmd.toUpperCase(Locale.ENGLISH).trim())) { return new GroupedOnlineAuc(); } return null; } @Override public void saveTo(OutputStream out) throws IOException { if (alr != null) { alr.close(); } setTargetCategories(getCsvRecordFactory().getTargetCategories()); write(new DataOutputStream(out)); } @Override public void write(DataOutput out) throws IOException { out.writeUTF(getTargetVariable()); out.writeInt(getTypeMap().size()); for (Map.Entry<String, String> entry : getTypeMap().entrySet()) { out.writeUTF(entry.getKey()); out.writeUTF(entry.getValue()); } out.writeInt(getNumFeatures()); out.writeInt(getMaxTargetCategories()); out.writeInt(getTargetCategories().size()); for (String category : getTargetCategories()) { out.writeUTF(category); } out.writeInt(interval); out.writeInt(averageWindow); out.writeInt(threads); out.writeUTF(prior); out.writeDouble(priorOption); out.writeUTF(auc); // skip csv alr.write(out); } @Override public void readFields(DataInput in) throws IOException { setTargetVariable(in.readUTF()); int typeMapSize = in.readInt(); Map<String, String> typeMap = new HashMap<String, String>(typeMapSize); for (int i = 0; i < typeMapSize; i++) { String key = in.readUTF(); String value = in.readUTF(); typeMap.put(key, value); } setTypeMap(typeMap); setNumFeatures(in.readInt()); setMaxTargetCategories(in.readInt()); int targetCategoriesSize = in.readInt(); List<String> targetCategories = Lists.newArrayListWithCapacity(targetCategoriesSize); for (int i = 0; i < targetCategoriesSize; i++) { targetCategories.add(in.readUTF()); } setTargetCategories(targetCategories); interval = in.readInt(); averageWindow = in.readInt(); threads = in.readInt(); prior = in.readUTF(); priorOption = in.readDouble(); auc = in.readUTF(); alr = new AdaptiveLogisticRegression(); alr.readFields(in); } private static AdaptiveLogisticModelParameters loadFromStream(InputStream in) throws IOException { AdaptiveLogisticModelParameters result = new AdaptiveLogisticModelParameters(); result.readFields(new DataInputStream(in)); return result; } public static AdaptiveLogisticModelParameters loadFromFile(File in) throws IOException { InputStream input = new FileInputStream(in); try { return loadFromStream(input); } finally { Closeables.close(input, true); } } public int getInterval() { return interval; } public void setInterval(int interval) { this.interval = interval; } public int getAverageWindow() { return averageWindow; } public void setAverageWindow(int averageWindow) { this.averageWindow = averageWindow; } public int getThreads() { return threads; } public void setThreads(int threads) { this.threads = threads; } public String getPrior() { return prior; } public void setPrior(String prior) { this.prior = prior; } public String getAuc() { return auc; } public void setAuc(String auc) { this.auc = auc; } public double getPriorOption() { return priorOption; } public void setPriorOption(double priorOption) { this.priorOption = priorOption; } }