This is an implementation of a single iteration of Lloyd's algorithm for kmeans. More...
Public Member Functions  
NaiveKMeans (const MatType &dataset, MetricType &metric)  
Construct the NaiveKMeans object with the given dataset and metric. More...  
size_t  DistanceCalculations () const 
double  Iterate (const arma::mat ¢roids, arma::mat &newCentroids, arma::Col< size_t > &counts) 
Run a single iteration of the Lloyd algorithm, updating the given centroids into the newCentroids matrix. More...  
This is an implementation of a single iteration of Lloyd's algorithm for kmeans.
If your intention is to run the full kmeans algorithm, you are looking for the mlpack::kmeans::KMeans class instead of this one. This class is used by KMeans as the actual implementation of the Lloyd iteration.
MetricType  Type of metric used with this implementation. 
MatType  Matrix type (arma::mat or arma::sp_mat). 
Definition at line 32 of file naive_kmeans.hpp.
NaiveKMeans  (  const MatType &  dataset, 
MetricType &  metric  
) 
Construct the NaiveKMeans object with the given dataset and metric.
dataset  Dataset. 
metric  Instantiated metric. 

inline 
Definition at line 57 of file naive_kmeans.hpp.
double Iterate  (  const arma::mat &  centroids, 
arma::mat &  newCentroids,  
arma::Col< size_t > &  counts  
) 
Run a single iteration of the Lloyd algorithm, updating the given centroids into the newCentroids matrix.
If any cluster is empty (that is, if any cluster has no points assigned to it), then the centroid associated with that cluster may be filled with invalid data (it will be corrected later).
centroids  Current cluster centroids. 
newCentroids  New cluster centroids. 
counts  Number of points in each cluster at the end of the iteration. 