org.apache.mahout.clustering.syntheticcontrol.kmeans

Class Job

java.lang.Object

org.apache.hadoop.conf.Configured

org.apache.mahout.common.AbstractJob

org.apache.mahout.clustering.syntheticcontrol.kmeans.Job

All Implemented Interfaces:

org.apache.hadoop.conf.Configurable, org.apache.hadoop.util.Tool

public final class Job
extends AbstractJob

Field Summary

Fields inherited from class org.apache.mahout.common.AbstractJob

argMap, inputFile, inputPath, outputFile, outputPath, tempPath

Method Summary

Modifier and Type	Method and Description
static void	main(String[] args)
static void	run(org.apache.hadoop.conf.Configuration conf, org.apache.hadoop.fs.Path input, org.apache.hadoop.fs.Path output, DistanceMeasure measure, double t1, double t2, double convergenceDelta, int maxIterations) Run the kmeans clustering job on an input dataset using the given distance measure, t1, t2 and iteration parameters.
static void	run(org.apache.hadoop.conf.Configuration conf, org.apache.hadoop.fs.Path input, org.apache.hadoop.fs.Path output, DistanceMeasure measure, int k, double convergenceDelta, int maxIterations) Run the kmeans clustering job on an input dataset using the given the number of clusters k and iteration parameters.
int	run(String[] args)

Methods inherited from class org.apache.mahout.common.AbstractJob

addFlag, addInputOption, addOption, addOption, addOption, addOption, addOutputOption, buildOption, buildOption, getAnalyzerClassFromOption, getCLIOption, getConf, getDimensions, getFloat, getFloat, getGroup, getInputFile, getInputPath, getInt, getInt, getOption, getOption, getOption, getOptions, getOutputFile, getOutputPath, getOutputPath, getTempPath, getTempPath, hasOption, keyFor, maybePut, parseArguments, parseArguments, parseDirectories, prepareJob, prepareJob, prepareJob, prepareJob, setConf, setS3SafeCombinedInputPath, shouldRunNextPhase

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

main

public static void main(String[] args)
                 throws Exception

Throws:

Exception

run

public int run(String[] args)
        throws Exception

Throws:

Exception

run

public static void run(org.apache.hadoop.conf.Configuration conf,
                       org.apache.hadoop.fs.Path input,
                       org.apache.hadoop.fs.Path output,
                       DistanceMeasure measure,
                       int k,
                       double convergenceDelta,
                       int maxIterations)
                throws Exception

Run the kmeans clustering job on an input dataset using the given the number of clusters k and iteration parameters. All output data will be written to the output directory, which will be initially deleted if it exists. The clustered points will reside in the path

/clustered-points. By default, the job expects a file containing equal length space delimited data that resides in a directory named "testdata", and writes output to a directory named "output".

Parameters:

conf - the Configuration to use

input - the String denoting the input directory path

output - the String denoting the output directory path

measure - the DistanceMeasure to use

k - the number of clusters in Kmeans

convergenceDelta - the double convergence criteria for iterations

maxIterations - the int maximum number of iterations

Throws:

Exception

run

public static void run(org.apache.hadoop.conf.Configuration conf,
                       org.apache.hadoop.fs.Path input,
                       org.apache.hadoop.fs.Path output,
                       DistanceMeasure measure,
                       double t1,
                       double t2,
                       double convergenceDelta,
                       int maxIterations)
                throws Exception

Run the kmeans clustering job on an input dataset using the given distance measure, t1, t2 and iteration parameters. All output data will be written to the output directory, which will be initially deleted if it exists. The clustered points will reside in the path

/clustered-points. By default, the job expects the a file containing synthetic_control.data as obtained from http://archive.ics.uci.edu/ml/datasets/Synthetic+Control+Chart+Time+Series resides in a directory named "testdata", and writes output to a directory named "output".

Parameters:

conf - the Configuration to use

input - the String denoting the input directory path

output - the String denoting the output directory path

measure - the DistanceMeasure to use

t1 - the canopy T1 threshold

t2 - the canopy T2 threshold

convergenceDelta - the double convergence criteria for iterations

maxIterations - the int maximum number of iterations

Throws:

Exception