org.apache.mahout.clustering.spectral.eigencuts
Class EigencutsDriver
java.lang.Object
org.apache.hadoop.conf.Configured
org.apache.mahout.common.AbstractJob
org.apache.mahout.clustering.spectral.eigencuts.EigencutsDriver
- All Implemented Interfaces:
- org.apache.hadoop.conf.Configurable, org.apache.hadoop.util.Tool
public class EigencutsDriver
- extends AbstractJob
Method Summary |
static void |
main(java.lang.String[] args)
|
static DistributedRowMatrix |
performEigenDecomposition(org.apache.hadoop.conf.Configuration conf,
DistributedRowMatrix input,
int numEigenVectors,
int overshoot,
java.util.List<java.lang.Double> eigenValues,
Matrix eigenVectors,
org.apache.hadoop.fs.Path tmp)
Does most of the heavy lifting in setting up Paths, configuring return
values, and generally performing the tedious administrative tasks involved
in an eigen-decomposition and running the verifier |
static void |
run(org.apache.hadoop.conf.Configuration conf,
org.apache.hadoop.fs.Path input,
org.apache.hadoop.fs.Path output,
int dimensions,
double halflife,
double epsilon,
double tau)
Run the Eigencuts clustering algorithm using the supplied arguments |
int |
run(java.lang.String[] arg0)
|
Methods inherited from class org.apache.mahout.common.AbstractJob |
addFlag, addInputOption, addOption, addOption, addOption, addOption, addOutputOption, 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 |
EPSILON_DEFAULT
public static final double EPSILON_DEFAULT
- See Also:
- Constant Field Values
TAU_DEFAULT
public static final double TAU_DEFAULT
- See Also:
- Constant Field Values
OVERSHOOT_MULTIPLIER
public static final double OVERSHOOT_MULTIPLIER
- See Also:
- Constant Field Values
EigencutsDriver
public EigencutsDriver()
main
public static void main(java.lang.String[] args)
throws java.lang.Exception
- Throws:
java.lang.Exception
run
public int run(java.lang.String[] arg0)
throws java.lang.Exception
- Throws:
java.lang.Exception
run
public static void run(org.apache.hadoop.conf.Configuration conf,
org.apache.hadoop.fs.Path input,
org.apache.hadoop.fs.Path output,
int dimensions,
double halflife,
double epsilon,
double tau)
throws java.io.IOException,
java.lang.InterruptedException,
java.lang.ClassNotFoundException
- Run the Eigencuts clustering algorithm using the supplied arguments
- Parameters:
conf
- the Configuration to useinput
- the Path to the directory containing input affinity tuplesoutput
- the Path to the output directorydimensions
- the int number of dimensions of the square affinity matrixhalflife
- the double minimum half-life thresholdepsilon
- the double coefficient for setting minimum half-life thresholdtau
- the double tau threshold for cutting links in the affinity graph
- Throws:
java.io.IOException
java.lang.InterruptedException
java.lang.ClassNotFoundException
performEigenDecomposition
public static DistributedRowMatrix performEigenDecomposition(org.apache.hadoop.conf.Configuration conf,
DistributedRowMatrix input,
int numEigenVectors,
int overshoot,
java.util.List<java.lang.Double> eigenValues,
Matrix eigenVectors,
org.apache.hadoop.fs.Path tmp)
throws java.io.IOException
- Does most of the heavy lifting in setting up Paths, configuring return
values, and generally performing the tedious administrative tasks involved
in an eigen-decomposition and running the verifier
- Throws:
java.io.IOException
Copyright © 2008-2010 The Apache Software Foundation. All Rights Reserved.