|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD | |||||||||
java.lang.Objectweka.clusterers.ClusterEvaluation
public class ClusterEvaluation
Class for evaluating clustering models.
Valid options are: -t name of the training fileweka.core.Drawable interface.
Drawable,
Serialized Form| Constructor Summary | |
|---|---|
ClusterEvaluation()
Constructor. |
|
| Method Summary | |
|---|---|
java.lang.String |
clusterResultsToString()
return the results of clustering. |
static double |
crossValidateModel(DensityBasedClusterer clusterer,
Instances data,
int numFolds,
java.util.Random random)
Perform a cross-validation for DensityBasedClusterer on a set of instances. |
static java.lang.String |
crossValidateModel(java.lang.String clustererString,
Instances data,
int numFolds,
java.lang.String[] options,
java.util.Random random)
Performs a cross-validation for a DensityBasedClusterer clusterer on a set of instances. |
boolean |
equals(java.lang.Object obj)
Tests whether the current evaluation object is equal to another evaluation object |
static java.lang.String |
evaluateClusterer(Clusterer clusterer,
java.lang.String[] options)
Evaluates a clusterer with the options given in an array of strings. |
void |
evaluateClusterer(Instances test)
Evaluate the clusterer on a set of instances. |
void |
evaluateClusterer(Instances test,
java.lang.String testFileName)
Evaluate the clusterer on a set of instances. |
int[] |
getClassesToClusters()
Return the array (ordered by cluster number) of minimum error class to cluster mappings |
double[] |
getClusterAssignments()
Return an array of cluster assignments corresponding to the most recent set of instances clustered. |
double |
getLogLikelihood()
Return the log likelihood corresponding to the most recent set of instances clustered. |
int |
getNumClusters()
Return the number of clusters found for the most recent call to evaluateClusterer |
java.lang.String |
getRevision()
Returns the revision string. |
static void |
main(java.lang.String[] args)
Main method for testing this class. |
static void |
mapClasses(int numClusters,
int lev,
int[][] counts,
int[] clusterTotals,
double[] current,
double[] best,
int error)
Finds the minimum error mapping of classes to clusters. |
void |
setClusterer(Clusterer clusterer)
set the clusterer |
| Methods inherited from class java.lang.Object |
|---|
getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public ClusterEvaluation()
| Method Detail |
|---|
public void setClusterer(Clusterer clusterer)
clusterer - the clusterer to usepublic java.lang.String clusterResultsToString()
public int getNumClusters()
public double[] getClusterAssignments()
public int[] getClassesToClusters()
public double getLogLikelihood()
double value
public void evaluateClusterer(Instances test)
throws java.lang.Exception
test - the set of instances to cluster
java.lang.Exception - if something goes wrong
public void evaluateClusterer(Instances test,
java.lang.String testFileName)
throws java.lang.Exception
test - the set of instances to clustertestFileName - the name of the test file for incremental testing,
if "" or null then not used
java.lang.Exception - if something goes wrong
public static void mapClasses(int numClusters,
int lev,
int[][] counts,
int[] clusterTotals,
double[] current,
double[] best,
int error)
numClusters - the number of clusterslev - the cluster being processedcounts - the counts of classes in clustersclusterTotals - the total number of examples in each clustercurrent - the current path through the class to cluster assignment
treebest - the best assignment path seenerror - accumulates the error for a particular path
public static java.lang.String evaluateClusterer(Clusterer clusterer,
java.lang.String[] options)
throws java.lang.Exception
clusterer - machine learning clustereroptions - the array of string containing the options
java.lang.Exception - if model could not be evaluated successfully
public static double crossValidateModel(DensityBasedClusterer clusterer,
Instances data,
int numFolds,
java.util.Random random)
throws java.lang.Exception
clusterer - the clusterer to usedata - the training datanumFolds - number of folds of cross validation to performrandom - random number seed for cross-validation
java.lang.Exception - if an error occurs
public static java.lang.String crossValidateModel(java.lang.String clustererString,
Instances data,
int numFolds,
java.lang.String[] options,
java.util.Random random)
throws java.lang.Exception
clustererString - a string naming the class of the clustererdata - the data on which the cross-validation is to be
performednumFolds - the number of folds for the cross-validationoptions - the options to the clustererrandom - a random number generator
java.lang.Exception - if a clusterer could not be generatedpublic boolean equals(java.lang.Object obj)
equals in class java.lang.Objectobj - the object to compare against
public java.lang.String getRevision()
getRevision in interface RevisionHandlerpublic static void main(java.lang.String[] args)
args - the options
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD | |||||||||