Uses of Class
com.gpudb.protocol.AggregateKMeansResponse

Packages that use AggregateKMeansResponse

Package	Description
com.gpudb
com.gpudb.protocol

Uses of AggregateKMeansResponse in com.gpudb

Methods in com.gpudb that return AggregateKMeansResponse

Modifier and Type	Method	Description
AggregateKMeansResponse	GPUdb.aggregateKMeans(AggregateKMeansRequest request)	This endpoint runs the k-means algorithm - a heuristic algorithm that attempts to do k-means clustering.
AggregateKMeansResponse	GPUdb.aggregateKMeans(String tableName, List<String> columnNames, int k, double tolerance, Map<String,String> options)	This endpoint runs the k-means algorithm - a heuristic algorithm that attempts to do k-means clustering.

Uses of AggregateKMeansResponse in com.gpudb.protocol

Methods in com.gpudb.protocol that return AggregateKMeansResponse

Modifier and Type	Method	Description
AggregateKMeansResponse	AggregateKMeansResponse.setCount(long count)	The total count of all the clusters - will be the size of the input table.
AggregateKMeansResponse	AggregateKMeansResponse.setCounts(List<Long> counts)	The number of elements in the cluster closest the corresponding k-means values.
AggregateKMeansResponse	AggregateKMeansResponse.setInfo(Map<String,String> info)	Additional information.
AggregateKMeansResponse	AggregateKMeansResponse.setMeans(List<List<Double>> means)	The k-mean values found.
AggregateKMeansResponse	AggregateKMeansResponse.setNumIters(int numIters)	The number of iterations the algorithm executed before it quit.
AggregateKMeansResponse	AggregateKMeansResponse.setRmsDist(double rmsDist)	The sum of all the rms_dists - the value the k-means algorithm is attempting to minimize.
AggregateKMeansResponse	AggregateKMeansResponse.setRmsDists(List<Double> rmsDists)	The root mean squared distance of the elements in the cluster for each of the k-means values.
AggregateKMeansResponse	AggregateKMeansResponse.setTolerance(double tolerance)	The distance between the last two iterations of the algorithm before it quit.