Package com.apple.foundationdb.kmeans
package com.apple.foundationdb.kmeans
k-means++ algorithm.
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ClassDescriptionA restartable Lloyd-style k-means++ implementation intended for LOCAL cluster restructuring (SPFresh-style).Outcome of a
fitcall: the chosen centroids, the per-vector cluster assignment, the per-cluster sizes, the per-vector objective contributions, and the total objective.Soft size-balancing penalty hook.Evaluates whether a candidate partitioning should replace a current partitioning.The verdictPartitionEvaluator.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.The outcome of evaluating a candidate partitioning against the current layout.Tuning parameters that control when a candidate repartitioning is accepted or rejected, and how the composite quality score is computed.Represents a partitioning of a set of vectors intokclusters, as passed toPartitionEvaluator.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).Quality statistics computed for a partitioning (current or candidate).