clustering.hpp File Reference

Clustering algorithms implementation. More...

#include <algorithm>
#include <cmath>
#include <cstddef>
#include <limits>
#include <map>
#include <numeric>
#include <random>
#include <stdexcept>
#include <utility>
#include <vector>
#include "statcpp/random_engine.hpp"

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Classes
struct	statcpp::kmeans_result
	K-means clustering result. More...
struct	statcpp::dendrogram_node
	Dendrogram node. More...

Namespaces
namespace	statcpp

Enumerations
enum class	statcpp::linkage_type { statcpp::single , statcpp::complete , statcpp::average , statcpp::ward }
	Linkage types. More...

Functions
double	statcpp::euclidean_distance (const std::vector< double > &a, const std::vector< double > &b)
	Euclidean distance.
double	statcpp::manhattan_distance (const std::vector< double > &a, const std::vector< double > &b)
	Manhattan distance.
std::vector< std::vector< double > >	statcpp::kmeans_plusplus_init (const std::vector< std::vector< double > > &data, std::size_t k)
	K-means++ initialization.
kmeans_result	statcpp::kmeans (const std::vector< std::vector< double > > &data, std::size_t k, std::size_t max_iter=100, double tol=1e-6)
	K-means clustering.
std::vector< dendrogram_node >	statcpp::hierarchical_clustering (const std::vector< std::vector< double > > &data, linkage_type linkage=linkage_type::single)
	Hierarchical clustering.
std::vector< std::size_t >	statcpp::cut_dendrogram (const std::vector< dendrogram_node > &dendrogram, std::size_t n_data, std::size_t k)
	Extract k clusters from dendrogram.
double	statcpp::silhouette_score (const std::vector< std::vector< double > > &data, const std::vector< std::size_t > &labels)
	Calculate silhouette score.

Detailed Description

Clustering algorithms implementation.

Provides K-means, hierarchical clustering, silhouette score, and related algorithms.

Definition in file clustering.hpp.