Uses of Interface
org.apache.mahout.common.kernel.IKernelProfile

Packages that use IKernelProfile
org.apache.mahout.clustering.meanshift   
org.apache.mahout.common.kernel   
 

Uses of IKernelProfile in org.apache.mahout.clustering.meanshift
 

Methods in org.apache.mahout.clustering.meanshift with parameters of type IKernelProfile
static org.apache.hadoop.fs.Path MeanShiftCanopyDriver.buildClusters(org.apache.hadoop.conf.Configuration conf, org.apache.hadoop.fs.Path clustersIn, org.apache.hadoop.fs.Path output, DistanceMeasure measure, IKernelProfile kernelProfile, double t1, double t2, double convergenceDelta, int maxIterations, boolean runSequential, boolean runClustering)
          Iterate over the input clusters to produce the next cluster directories for each iteration
static List<MeanShiftCanopy> MeanShiftCanopyClusterer.clusterPoints(Iterable<Vector> points, DistanceMeasure measure, IKernelProfile aKernelProfileDerivative, double convergenceThreshold, double t1, double t2, int numIter)
          This is the reference mean-shift implementation.
static void MeanShiftCanopyDriver.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, boolean inputIsCanopies, boolean runClustering, boolean runSequential)
          Run the job where the input format can be either Vectors or Canopies.
 

Constructors in org.apache.mahout.clustering.meanshift with parameters of type IKernelProfile
MeanShiftCanopyClusterer(DistanceMeasure aMeasure, IKernelProfile aKernelProfileDerivative, double aT1, double aT2, double aDelta, boolean runClustering)
           
 

Uses of IKernelProfile in org.apache.mahout.common.kernel
 

Classes in org.apache.mahout.common.kernel that implement IKernelProfile
 class NormalKernelProfile
           
 class TriangularKernelProfile
           
 



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