Package com.apple.foundationdb.kmeans

package com.apple.foundationdb.kmeans

k-means++ algorithm.

Related Packages

Package	Description
com.apple.foundationdb	FDB client code that might conceivably be in the standard Java binding someday.

Class	Description
KMeans	A restartable Lloyd-style k-means++ implementation intended for LOCAL cluster restructuring (SPFresh-style).
KMeans.Result<C>	Outcome of a fit call: the chosen centroids, the per-vector cluster assignment, the per-cluster sizes, the per-vector objective contributions, and the total objective.
KMeans.SizePenalty	Soft size-balancing penalty hook.
PartitionEvaluator	Evaluates whether a candidate partitioning should replace a current partitioning.
PartitionEvaluator.Decision	The verdict PartitionEvaluator.evaluate(java.util.List<V>, com.apple.foundationdb.kmeans.PartitionEvaluator.Partition<?>, java.util.List<V>, com.apple.foundationdb.kmeans.PartitionEvaluator.Partition<?>, com.apple.foundationdb.util.Lens<V, com.apple.foundationdb.linear.RealVector>, com.apple.foundationdb.kmeans.PartitionEvaluator.Parameters) returns about a candidate partitioning relative to the current one.
PartitionEvaluator.EvaluationResult	The outcome of evaluating a candidate partitioning against the current layout.
PartitionEvaluator.Parameters	Tuning parameters that control when a candidate repartitioning is accepted or rejected, and how the composite quality score is computed.
PartitionEvaluator.Partition<V>	Represents a partitioning of a set of vectors into k clusters, as passed to PartitionEvaluator.evaluate(java.util.List<V>, com.apple.foundationdb.kmeans.PartitionEvaluator.Partition<?>, java.util.List<V>, com.apple.foundationdb.kmeans.PartitionEvaluator.Partition<?>, com.apple.foundationdb.util.Lens<V, com.apple.foundationdb.linear.RealVector>, com.apple.foundationdb.kmeans.PartitionEvaluator.Parameters).
PartitionEvaluator.PartitionStats	Quality statistics computed for a partitioning (current or candidate).