This is an implementation of a single iteration of Lloyd's algorithm for k-means. More...
|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 k-means.
If your intention is to run the full k-means 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).|
|NaiveKMeans||(||const MatType &||dataset,|
Construct the NaiveKMeans object with the given dataset and metric.
|double Iterate||(||const arma::mat &||centroids,|
|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.|