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Oracle Data Mining Java API Reference
11g Release 2 (11.2)

E12219-01


oracle.dmt.jdm.algorithm.kmeans
Class OraClusteringDistanceFunction

java.lang.Object
  extended byoracle.dmt.jdm.algorithm.kmeans.OraClusteringDistanceFunction


public class OraClusteringDistanceFunction
extends java.lang.Object

This class defines Oracle extensions to standard ClusteringDistanceFunction enumerations. Oracle supports cosine and fast_cosine distance functions in addition to euclidean function. By default euclidean distance function is used by the algorithm. Specified distance function is used as the metric to determine the similarity between the data points.

See Also:
ClusteringDistanceFunction

Field Summary
static javax.datamining.algorithm.kmeans.ClusteringDistanceFunction cosine
          Setting value representing cosine distance function.
static javax.datamining.algorithm.kmeans.ClusteringDistanceFunction fastCosine
          Setting value representing fast cosine distance function.

 

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

 

Field Detail

cosine

public static final javax.datamining.algorithm.kmeans.ClusteringDistanceFunction cosine
Setting value representing cosine distance function.

fastCosine

public static final javax.datamining.algorithm.kmeans.ClusteringDistanceFunction fastCosine
Setting value representing fast cosine distance function.

Skip navigation links

Oracle Data Mining Java API Reference
11g Release 2 (11.2)

E12219-01


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