kmeans::Initialize< Matrix_, Cluster_, Float_ > Class Template Reference

Base class for initialization algorithms. More...

#include <Initialize.hpp>

Inheritance diagram for kmeans::Initialize< Matrix_, Cluster_, Float_ >:

Public Member Functions
virtual Cluster_	run (const Matrix_ &data, Cluster_ num_centers, Float_ *centers) const =0

Detailed Description

template<class Matrix_ = SimpleMatrix<double, int>, typename Cluster_ = int, typename Float_ = double>
class kmeans::Initialize< Matrix_, Cluster_, Float_ >

Base class for initialization algorithms.

Template Parameters

Matrix_	Matrix type for the input data. This should satisfy the MockMatrix contract.
Cluster_	Integer type for the cluster assignments.
Float_	Floating-point type for the centroids.

Member Function Documentation

run()

template<class Matrix_ = SimpleMatrix<double, int>, typename Cluster_ = int, typename Float_ = double>

virtual Cluster_ kmeans::Initialize< Matrix_, Cluster_, Float_ >::run ( const Matrix_ &  data, Cluster_  num_centers, Float_ *  centers  ) const

pure virtual

Parameters

	data	A matrix-like object (see MockMatrix) containing per-observation data.
	num_centers	Number of cluster centers.
[out]	centers	Pointer to an array of length equal to the product of num_centers and data.num_dimensions(). This contains a column-major matrix where rows correspond to dimensions and columns correspond to cluster centers. On output, each column will contain the final centroid locations for each cluster.

Returns

centers is filled with the new cluster centers. The number of filled centers is returned - this is usually equal to num_centers, but may not be if, e.g., num_centers is greater than the number of observations. If the returned value is less than num_centers, only the first few centers in centers will be filled.

Implemented in kmeans::InitializeRandom< Matrix_, Cluster_, Float_ >, kmeans::InitializeVariancePartition< Matrix_, Cluster_, Float_ >, kmeans::InitializeNone< Matrix_, Cluster_, Float_ >, and kmeans::InitializeKmeanspp< Matrix_, Cluster_, Float_ >.

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The documentation for this class was generated from the following file:

• kmeans/Initialize.hpp