nk 1.0.0
C++ Numerical Computing Runtime
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kmedoids.hpp
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1
3// toolboxes/stats/include/nk/stats/cluster/kmedoids.hpp
4
5#pragma once
6
7#include <memory_resource>
8#include <nk/value/value.hpp>
9
10#include <string>
11#include <tuple>
12
13namespace nk {
14
17 namespace ops { class RngContext; } }
18
19namespace nk::stats {
20
36std::tuple<Value, Value, Value>
37kmedoids(::nk::ops::RngContext &rng, const Value &X, int K, int max_iter, int replicates,
38 const std::string &metric,
39 std::pmr::memory_resource *mr = nullptr);
40
60std::tuple<Value, Value>
61dbscan(const Value &X, double eps, int minpts, const std::string &metric,
62 std::pmr::memory_resource *mr = nullptr);
63
67std::tuple<Value, Value>
68dbscan(const Value &X, double eps, int minpts, const std::string &metric,
69 double p,
70 std::pmr::memory_resource *mr = nullptr);
71
72
74} // namespace nk::stats
nk::Value
Core MATLAB-compatible multidimensional array and scalar value type.
Definition value.hpp:61
nk::stats::dbscan
std::tuple< Value, Value > dbscan(const Value &X, double eps, int minpts, const std::string &metric, std::pmr::memory_resource *mr=nullptr)
DBSCAN density-based clustering ([idx, corepts] = dbscan(X, eps, minpts, metric)).
nk::stats::kmedoids
std::tuple< Value, Value, Value > kmedoids(::nk::ops::RngContext &rng, const Value &X, int K, int max_iter, int replicates, const std::string &metric, std::pmr::memory_resource *mr=nullptr)
PAM-style k-medoids clustering ([idx, medoids, sumd] = kmedoids(...)).