AP_affinity_propagation |
Affinity propagation clustering |
AP_preferenceRange |
Affinity propagation preference range |
center_scale |
Function to scale and/or center the data |
Clara_Medoids |
Clustering large applications |
Cluster_Medoids |
Partitioning around medoids |
cost_clusters_from_dissim_medoids |
Compute the cost and clusters based on an input dissimilarity matrix and medoids |
dietary_survey_IBS |
Synthetic data using a dietary survey of patients with irritable bowel syndrome (IBS) |
distance_matrix |
Distance matrix calculation |
external_validation |
external clustering validation |
GMM |
Gaussian Mixture Model clustering |
KMeans_arma |
k-means using the Armadillo library |
KMeans_rcpp |
k-means using RcppArmadillo |
MiniBatchKmeans |
Mini-batch-k-means using RcppArmadillo |
mushroom |
The mushroom data |
Optimal_Clusters_GMM |
Optimal number of Clusters for the gaussian mixture models |
Optimal_Clusters_KMeans |
Optimal number of Clusters for Kmeans or Mini-Batch-Kmeans |
Optimal_Clusters_Medoids |
Optimal number of Clusters for the partitioning around Medoids functions |
plot_2d |
2-dimensional plots |
predict.GMMCluster |
Prediction function for a Gaussian Mixture Model object |
predict.KMeansCluster |
Prediction function for the k-means |
predict.MBatchKMeans |
Prediction function for Mini-Batch-k-means |
predict.MedoidsCluster |
Predictions for the Medoid functions |
predict_GMM |
Prediction function for a Gaussian Mixture Model object |
predict_KMeans |
Prediction function for the k-means |
predict_MBatchKMeans |
Prediction function for Mini-Batch-k-means |
predict_Medoids |
Predictions for the Medoid functions |
Silhouette_Dissimilarity_Plot |
Plot of silhouette widths or dissimilarities |
silhouette_of_clusters |
Silhouette width based on pre-computed clusters |
soybean |
The soybean (large) data set from the UCI repository |