kmeans
k-means clustering in C++
Loading...
Searching...
No Matches
kmeans::RefineHartiganWongOptions Struct Reference

Options for RefineHartiganWong. More...

#include <RefineHartiganWong.hpp>

Public Attributes

int max_iterations = 10
 
int max_quick_transfer_iterations = 50
 
bool quit_on_quick_transfer_convergence_failure = false
 
int num_threads = 1
 

Detailed Description

Options for RefineHartiganWong.

Member Data Documentation

◆ max_iterations

int kmeans::RefineHartiganWongOptions::max_iterations = 10

Maximum number of optimal transfer iterations. More iterations increase the opportunity for convergence at the cost of more compute time.

◆ max_quick_transfer_iterations

int kmeans::RefineHartiganWongOptions::max_quick_transfer_iterations = 50

Maximum number of quick transfer iterations. More iterations increase the opportunity for convergence at the cost of more compute time.

◆ num_threads

int kmeans::RefineHartiganWongOptions::num_threads = 1

Number of threads to use. The parallelization scheme is defined by parallelize().

◆ quit_on_quick_transfer_convergence_failure

bool kmeans::RefineHartiganWongOptions::quit_on_quick_transfer_convergence_failure = false

Whether to quit early when the number of quick transfer iterations exceeds RefineHartiganWongOptions::max_quick_tranfer_iterations. Setting this to true recovers the default behavior of R's kmeans() implementation. If false, the algorithm will ignore any convergence failures during the quick transfer step and procced to the next optimal transfer iteration. This provides another opportunity to improve the clustering (and potentially achieve convergence) at the cost of more compute time.


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