kmeans
A C++ library for k-means
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Public Member Functions | List of all members
kmeans::InitializeRandom< Matrix_, Cluster_, Float_ > Class Template Reference

Initialize by sampling random observations without replacement. More...

#include <InitializeRandom.hpp>

Inheritance diagram for kmeans::InitializeRandom< Matrix_, Cluster_, Float_ >:
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Public Member Functions

 InitializeRandom (InitializeRandomOptions options)
 
 InitializeRandom ()=default
 
InitializeRandomOptionsget_options ()
 
Cluster_ run (const Matrix_ &data, Cluster_ ncenters, Float_ *centers) const
 

Detailed Description

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

Initialize by sampling random observations without replacement.

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.

Constructor & Destructor Documentation

◆ InitializeRandom() [1/2]

template<class Matrix_ = SimpleMatrix<double, int>, typename Cluster_ = int, typename Float_ = double>
kmeans::InitializeRandom< Matrix_, Cluster_, Float_ >::InitializeRandom ( InitializeRandomOptions  options)
inline
Parameters
optionsOptions for random initialization.

◆ InitializeRandom() [2/2]

template<class Matrix_ = SimpleMatrix<double, int>, typename Cluster_ = int, typename Float_ = double>
kmeans::InitializeRandom< Matrix_, Cluster_, Float_ >::InitializeRandom ( )
default

Default constructor.

Member Function Documentation

◆ get_options()

template<class Matrix_ = SimpleMatrix<double, int>, typename Cluster_ = int, typename Float_ = double>
InitializeRandomOptions & kmeans::InitializeRandom< Matrix_, Cluster_, Float_ >::get_options ( )
inline
Returns
Options for random initialization, to be modified prior to calling run().

◆ run()

template<class Matrix_ = SimpleMatrix<double, int>, typename Cluster_ = int, typename Float_ = double>
Cluster_ kmeans::InitializeRandom< Matrix_, Cluster_, Float_ >::run ( const Matrix_ data,
Cluster_  num_centers,
Float_ centers 
) const
inlinevirtual
Parameters
dataA matrix-like object (see MockMatrix) containing per-observation data.
num_centersNumber of cluster centers.
[out]centersPointer 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.

Implements kmeans::Initialize< Matrix_, Cluster_, Float_ >.


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