/*
* 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.df.mapreduce;
import java.io.IOException;
import java.util.Random;
import org.apache.commons.cli2.CommandLine;
import org.apache.commons.cli2.Group;
import org.apache.commons.cli2.Option;
import org.apache.commons.cli2.OptionException;
import org.apache.commons.cli2.builder.ArgumentBuilder;
import org.apache.commons.cli2.builder.DefaultOptionBuilder;
import org.apache.commons.cli2.builder.GroupBuilder;
import org.apache.commons.cli2.commandline.Parser;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import org.apache.mahout.common.CommandLineUtil;
import org.apache.mahout.common.RandomUtils;
import org.apache.mahout.df.DFUtils;
import org.apache.mahout.df.DecisionForest;
import org.apache.mahout.df.ErrorEstimate;
import org.apache.mahout.df.builder.DefaultTreeBuilder;
import org.apache.mahout.df.callback.ForestPredictions;
import org.apache.mahout.df.data.Data;
import org.apache.mahout.df.data.DataLoader;
import org.apache.mahout.df.data.Dataset;
import org.apache.mahout.df.mapreduce.inmem.InMemBuilder;
import org.apache.mahout.df.mapreduce.partial.PartialBuilder;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* Tool to builds a Random Forest using any given dataset (in UCI format). Can use either the in-mem mapred or
* partial mapred implementations. Stores the forest in the given output directory
*/
public class BuildForest extends Configured implements Tool {
private static final Logger log = LoggerFactory.getLogger(BuildForest.class);
private Path dataPath;
private Path datasetPath;
private Path outputPath;
private int m; // Number of variables to select at each tree-node
private int nbTrees; // Number of trees to grow
private Long seed; // Random seed
private boolean isPartial; // use partial data implementation
private boolean isOob; // estimate oob error;
@Override
public int run(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
ArgumentBuilder abuilder = new ArgumentBuilder();
GroupBuilder gbuilder = new GroupBuilder();
Option oobOpt = obuilder.withShortName("oob").withRequired(false).withDescription(
"Optional, estimate the out-of-bag error").create();
Option dataOpt = obuilder.withLongName("data").withShortName("d").withRequired(true).withArgument(
abuilder.withName("path").withMinimum(1).withMaximum(1).create()).withDescription("Data path").create();
Option datasetOpt = obuilder.withLongName("dataset").withShortName("ds").withRequired(true).withArgument(
abuilder.withName("dataset").withMinimum(1).withMaximum(1).create()).withDescription("Dataset path")
.create();
Option selectionOpt = obuilder.withLongName("selection").withShortName("sl").withRequired(true)
.withArgument(abuilder.withName("m").withMinimum(1).withMaximum(1).create()).withDescription(
"Number of variables to select randomly at each tree-node").create();
Option seedOpt = obuilder.withLongName("seed").withShortName("sd").withRequired(false).withArgument(
abuilder.withName("seed").withMinimum(1).withMaximum(1).create()).withDescription(
"Optional, seed value used to initialise the Random number generator").create();
Option partialOpt = obuilder.withLongName("partial").withShortName("p").withRequired(false)
.withDescription("Optional, use the Partial Data implementation").create();
Option nbtreesOpt = obuilder.withLongName("nbtrees").withShortName("t").withRequired(true).withArgument(
abuilder.withName("nbtrees").withMinimum(1).withMaximum(1).create()).withDescription(
"Number of trees to grow").create();
Option outputOpt = obuilder.withLongName("output").withShortName("o").withRequired(true).withArgument(
abuilder.withName("path").withMinimum(1).withMaximum(1).create()).
withDescription("Output path, will contain the Decision Forest").create();
Option helpOpt = obuilder.withLongName("help").withDescription("Print out help").withShortName("h")
.create();
Group group = gbuilder.withName("Options").withOption(oobOpt).withOption(dataOpt).withOption(datasetOpt)
.withOption(selectionOpt).withOption(seedOpt).withOption(partialOpt).withOption(nbtreesOpt)
.withOption(outputOpt).withOption(helpOpt).create();
try {
Parser parser = new Parser();
parser.setGroup(group);
CommandLine cmdLine = parser.parse(args);
if (cmdLine.hasOption("help")) {
CommandLineUtil.printHelp(group);
return -1;
}
isPartial = cmdLine.hasOption(partialOpt);
isOob = cmdLine.hasOption(oobOpt);
String dataName = cmdLine.getValue(dataOpt).toString();
String datasetName = cmdLine.getValue(datasetOpt).toString();
String outputName = cmdLine.getValue(outputOpt).toString();
m = Integer.parseInt(cmdLine.getValue(selectionOpt).toString());
nbTrees = Integer.parseInt(cmdLine.getValue(nbtreesOpt).toString());
if (cmdLine.hasOption(seedOpt)) {
seed = Long.valueOf(cmdLine.getValue(seedOpt).toString());
}
log.debug("data : {}", dataName);
log.debug("dataset : {}", datasetName);
log.debug("output : {}", outputName);
log.debug("m : {}", m);
log.debug("seed : {}", seed);
log.debug("nbtrees : {}", nbTrees);
log.debug("isPartial : {}", isPartial);
log.debug("isOob : {}", isOob);
dataPath = new Path(dataName);
datasetPath = new Path(datasetName);
outputPath = new Path(outputName);
} catch (OptionException e) {
log.error("Exception", e);
CommandLineUtil.printHelp(group);
return -1;
}
buildForest();
return 0;
}
private void buildForest() throws IOException, ClassNotFoundException, InterruptedException {
// make sure the output path does not exist
FileSystem ofs = outputPath.getFileSystem(getConf());
if (ofs.exists(outputPath)) {
log.error("Output path already exists");
return;
}
DefaultTreeBuilder treeBuilder = new DefaultTreeBuilder();
treeBuilder.setM(m);
Dataset dataset = Dataset.load(getConf(), datasetPath);
ForestPredictions callback = isOob ? new ForestPredictions(dataset.nbInstances(), dataset.nblabels())
: null;
Builder forestBuilder;
if (isPartial) {
log.info("Partial Mapred implementation");
forestBuilder = new PartialBuilder(treeBuilder, dataPath, datasetPath, seed, getConf());
} else {
log.info("InMem Mapred implementation");
forestBuilder = new InMemBuilder(treeBuilder, dataPath, datasetPath, seed, getConf());
}
forestBuilder.setOutputDirName(outputPath.getName());
log.info("Building the forest...");
long time = System.currentTimeMillis();
DecisionForest forest = forestBuilder.build(nbTrees, callback);
time = System.currentTimeMillis() - time;
log.info("Build Time: {}", DFUtils.elapsedTime(time));
log.info("Forest num Nodes: {}", forest.nbNodes());
log.info("Forest mean num Nodes: {}", forest.meanNbNodes());
log.info("Forest mean max Depth: {}", forest.meanMaxDepth());
if (isOob) {
Random rng;
if (seed != null) {
rng = RandomUtils.getRandom(seed);
} else {
rng = RandomUtils.getRandom();
}
FileSystem fs = dataPath.getFileSystem(getConf());
int[] labels = Data.extractLabels(dataset, fs, dataPath);
log.info("oob error estimate : "
+ ErrorEstimate.errorRate(labels, callback.computePredictions(rng)));
}
// store the decision forest in the output path
Path forestPath = new Path(outputPath, "forest.seq");
log.info("Storing the forest in: " + forestPath);
DFUtils.storeWritable(getConf(), forestPath, forest);
}
protected static Data loadData(Configuration conf, Path dataPath, Dataset dataset) throws IOException {
log.info("Loading the data...");
FileSystem fs = dataPath.getFileSystem(conf);
Data data = DataLoader.loadData(dataset, fs, dataPath);
log.info("Data Loaded");
return data;
}
/**
* @param args
* @throws Exception
*/
public static void main(String[] args) throws Exception {
ToolRunner.run(new Configuration(), new BuildForest(), args);
}
}