MachineLearning.Clustering

Contents

Description

Cluster Analysis a.k.a. Clustering - grouping data into coherent subsets.

Synopsis

Documentation

Cluster type (list of samples associtaed with the cluster).

Arguments

:: RandomGen g
=> Int	number of K-Means Algorithm runs (`N`);
-> Matrix	data to cluster;
-> Int	desired number of clusters (`K`);
-> Rand g (Vector Cluster)	list of clusters inside Random Monad.

Clusters data using K-Means Algorithm inside Random Monad. Runs K-Means algorithm N times, returns the clustering with smaller cost.

Exported for testing purposes only.

Arguments

:: RandomGen g
=> Vector Vector	list of samples;
-> Int	number of clusters (`K`);
-> Int	iteration number;
-> Rand g (Vector Cluster, [R])	(list of clusters, cost values) inside Random Monad.

Run K-Means algorithm once inside Random Monad.