Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering
Affinity propagation clustering
Distance matrix calculation
entropy formula (used in external_validation function)
Affinity propagation preference range
Function to scale and/or center the data
Clustering large applications
Partitioning around medoids
Compute the cost and clusters based on an input dissimilarity matrix a...
external clustering validation
Interactive function for consecutive plots ( using dissimilarities or ...
Gaussian Mixture Model clustering
k-means using the Armadillo library
k-means using RcppArmadillo
Mini-batch-k-means using RcppArmadillo
Optimal number of Clusters for the gaussian mixture models
Optimal number of Clusters for Kmeans or Mini-Batch-Kmeans
Optimal number of Clusters for the partitioning around Medoids functio...
2-dimensional plots
Prediction function for a Gaussian Mixture Model object
Prediction function for the k-means
Prediction function for Mini-Batch-k-means
Predictions for the Medoid functions
Plot of silhouette widths or dissimilarities
Silhouette width based on pre-computed clusters
tryCatch function to prevent armadillo errors
tryCatch function to prevent armadillo errors in KMEANS_arma
tryCatch function to prevent armadillo errors in GMM_arma_AIC_BIC
Gaussian mixture models, k-means, mini-batch-kmeans, k-medoids and affinity propagation clustering with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. The package takes advantage of 'RcppArmadillo' to speed up the computationally intensive parts of the functions. For more information, see (i) "Clustering in an Object-Oriented Environment" by Anja Struyf, Mia Hubert, Peter Rousseeuw (1997), Journal of Statistical Software, <doi:10.18637/jss.v001.i04>; (ii) "Web-scale k-means clustering" by D. Sculley (2010), ACM Digital Library, <doi:10.1145/1772690.1772862>; (iii) "Armadillo: a template-based C++ library for linear algebra" by Sanderson et al (2016), The Journal of Open Source Software, <doi:10.21105/joss.00026>; (iv) "Clustering by Passing Messages Between Data Points" by Brendan J. Frey and Delbert Dueck, Science 16 Feb 2007: Vol. 315, Issue 5814, pp. 972-976, <doi:10.1126/science.1136800>.