org.apache.mahout.cf.taste.hadoop.als
Class ParallelALSFactorizationJob
java.lang.Object
org.apache.hadoop.conf.Configured
org.apache.mahout.common.AbstractJob
org.apache.mahout.cf.taste.hadoop.als.ParallelALSFactorizationJob
- All Implemented Interfaces:
- org.apache.hadoop.conf.Configurable, org.apache.hadoop.util.Tool
public class ParallelALSFactorizationJob
- extends AbstractJob
MapReduce implementation of the factorization algorithm described in
"Large-scale Parallel Collaborative Filtering for the Netflix Prize"
available at
http://www.hpl.hp.com/personal/Robert_Schreiber/papers/2008%20AAIM%20Netflix/netflix_aaim08(submitted).pdf.
Implements a parallel algorithm that uses "Alternating-Least-Squares with Weighted-λ-Regularization"
to factorize the preference-matrix
Command line arguments specific to this class are:
- --input (path): Directory containing one or more text files with the dataset
- --output (path): path where output should go
- --lambda (double): regularization parameter to avoid overfitting
- --numFeatures (int): number of features to use for decomposition
- --numIterations (int): number of iterations to run
Methods inherited from class org.apache.mahout.common.AbstractJob |
addFlag, addInputOption, addOption, addOption, addOption, addOption, addOutputOption, buildOption, getInputPath, getOption, getOutputPath, hasOption, keyFor, maybePut, parseArguments, parseDirectories, prepareJob, shouldRunNextPhase |
Methods inherited from class org.apache.hadoop.conf.Configured |
getConf, setConf |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Methods inherited from interface org.apache.hadoop.conf.Configurable |
getConf, setConf |
ParallelALSFactorizationJob
public ParallelALSFactorizationJob()
main
public static void main(String[] args)
throws Exception
- Throws:
Exception
run
public int run(String[] args)
throws Exception
- Throws:
Exception
Copyright © 2008-2011 The Apache Software Foundation. All Rights Reserved.