Package | Description |
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org.apache.mahout.clustering.streaming.cluster | |
org.apache.mahout.clustering.streaming.mapreduce | |
org.apache.mahout.math.neighborhood |
Modifier and Type | Method and Description |
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UpdatableSearcher |
StreamingKMeans.cluster(Centroid datapoint)
Cluster one data point.
|
UpdatableSearcher |
StreamingKMeans.cluster(Iterable<Centroid> datapoints)
Cluster the data points in an Iterable
|
UpdatableSearcher |
BallKMeans.cluster(List<? extends WeightedVector> datapoints)
Clusters the datapoints in the list doing either random seeding of the centroids or k-means++.
|
UpdatableSearcher |
StreamingKMeans.cluster(Matrix data)
Cluster the rows of a matrix, treating them as Centroids with weight 1.
|
Constructor and Description |
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BallKMeans(UpdatableSearcher searcher,
int numClusters,
int maxNumIterations) |
BallKMeans(UpdatableSearcher searcher,
int numClusters,
int maxNumIterations,
boolean kMeansPlusPlusInit,
int numRuns) |
BallKMeans(UpdatableSearcher searcher,
int numClusters,
int maxNumIterations,
double trimFraction,
boolean kMeansPlusPlusInit,
boolean correctWeights,
double testProbability,
int numRuns) |
StreamingKMeans(UpdatableSearcher searcher,
int numClusters)
Calls StreamingKMeans(searcher, numClusters, 1.3, 10, 2).
|
StreamingKMeans(UpdatableSearcher searcher,
int numClusters,
double distanceCutoff)
Calls StreamingKMeans(searcher, numClusters, distanceCutoff, 1.3, 10, 2).
|
StreamingKMeans(UpdatableSearcher searcher,
int numClusters,
double distanceCutoff,
double beta,
double clusterLogFactor,
double clusterOvershoot)
Creates a new StreamingKMeans class given a searcher and the number of clusters to generate.
|
Modifier and Type | Method and Description |
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static UpdatableSearcher |
StreamingKMeansUtilsMR.searcherFromConfiguration(org.apache.hadoop.conf.Configuration conf)
Instantiates a searcher from a given configuration.
|
Modifier and Type | Class and Description |
---|---|
class |
BruteSearch
Search for nearest neighbors using a complete search (i.e.
|
class |
FastProjectionSearch
Does approximate nearest neighbor search by projecting the vectors similar to ProjectionSearch.
|
class |
LocalitySensitiveHashSearch
Implements a Searcher that uses locality sensitivity hash as a first pass approximation
to estimate distance without floating point math.
|
class |
ProjectionSearch
Does approximate nearest neighbor dudes search by projecting the data.
|
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