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 |