org.apache.mahout.clustering.syntheticcontrol.meanshift
Class Job
java.lang.Object
org.apache.hadoop.conf.Configured
org.apache.mahout.common.AbstractJob
org.apache.mahout.clustering.syntheticcontrol.meanshift.Job
- All Implemented Interfaces:
- org.apache.hadoop.conf.Configurable, org.apache.hadoop.util.Tool
public final class Job
- extends AbstractJob
Method Summary |
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,
IKernelProfile kernelProfile,
double t1,
double t2,
double convergenceDelta,
int maxIterations)
Run the meanshift clustering job on an input dataset using the given
distance measure, t1, t2 and iteration parameters. |
int |
run(String[] args)
|
Methods inherited from class org.apache.mahout.common.AbstractJob |
addFlag, addInputOption, addOption, addOption, addOption, addOption, addOutputOption, buildOption, getAnalyzerClassFromOption, getCLIOption, getCombinedTempPath, getGroup, getInputPath, getOption, getOption, getOutputPath, getOutputPath, getTempPath, getTempPath, hasOption, keyFor, maybePut, parseArguments, parseDirectories, prepareJob, prepareJob, prepareJob, setS3SafeCombinedInputPath, 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 |
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,
IKernelProfile kernelProfile,
double t1,
double t2,
double convergenceDelta,
int maxIterations)
throws Exception
- Run the meanshift 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
Copyright © 2008-2012 The Apache Software Foundation. All Rights Reserved.