HierarchicalClustering Class Reference

Agglomerative Hierarchical Clustering for clustering tasks. More...

#include <HierarchicalClustering.hpp>

Public Types
enum class	Linkage { SINGLE , COMPLETE , AVERAGE }
	Linkage criteria for clustering.

Public Member Functions
	HierarchicalClustering (int n_clusters=2, Linkage linkage=Linkage::AVERAGE)
	Constructs a HierarchicalClustering instance. More...
	~HierarchicalClustering ()
	Destructor for HierarchicalClustering.
void	fit (const std::vector< std::vector< double >> &X)
	Fits the clustering algorithm to the data. More...
std::vector< int >	predict () const
	Predicts the cluster labels for the data. More...
std::vector< std::vector< double > >	get_cluster_centers () const
	Retrieves the cluster centers (centroids) after fitting. More...

Detailed Description

Agglomerative Hierarchical Clustering for clustering tasks.

Constructor & Destructor Documentation

HierarchicalClustering()

HierarchicalClustering::HierarchicalClustering	(	int	n_clusters = 2,
		Linkage	linkage = Linkage::AVERAGE
	)

Constructs a HierarchicalClustering instance.

Parameters

n_clusters	The number of clusters to form.
linkage	The linkage criterion to use.

Member Function Documentation

fit()

void HierarchicalClustering::fit

(

const std::vector< std::vector< double >> &

X

)

Fits the clustering algorithm to the data.

Parameters

X	A vector of feature vectors (data points).

get_cluster_centers()

std::vector< std::vector< double > > HierarchicalClustering::get_cluster_centers

(

)

const

Retrieves the cluster centers (centroids) after fitting.

Returns

A vector of cluster centroids.

predict()

std::vector< int > HierarchicalClustering::predict

(

)

const

Predicts the cluster labels for the data.

Returns

A vector of cluster labels.

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

• ml_library_include/ml/clustering/HierarchicalClustering.hpp