What is Mclust package?
Introduction. mclust is a contributed R package for model-based clustering, classification, and density estimation based on finite normal mixture modelling. Additional functionalities are available for displaying and visualizing fitted models along with clustering, classification, and density estimation results.
What is mclust?
mclust is a popular R package for model-based clustering, classification, and density estimation based on finite Gaussian mixture modelling. Additional ways of displaying and visualising fitted models along with clustering, classification, and density estimation results are also provided.
What is BIC Mclust?
r clustering gaussian-mixture-distribution bic model-based-clustering. The R package mclust uses BIC as a criteria for cluster model selection. From my understanding, a model with the lowest BIC should be selected over other models (if you solely only care about BIC).
What kind of functions are included in mclust?
Also included are functions that combine model-based hierarchical clustering, EM for mixture estimation and the Bayesian Information Criterion (BIC) in comprehensive strategies for clustering, density estimation and discriminant analysis.
How is model based clustering used in mclust?
Model-based clustering based on parameterized finite Gaussian mixture models. Models are estimated by EM algorithm initialized by hierarchical model-based agglomerative clustering. The optimal model is then selected according to BIC.
When to use the second option in mclust?
The first option controls colors used for plotting BIC, ICL, etc. curves, whereas the second option is used to assign colors for indicating clusters or classes when plotting data. Starting with version 4.0, the function can be used for retrieving colors from some pre-defined palettes. For instance
Can a categorical variable be used in mclust?
A numeric vector, matrix, or data frame of observations. Categorical variables are not allowed. If a matrix or data frame, rows correspond to observations ( n) and columns correspond to variables ( d ). An integer vector specifying the numbers of mixture components (clusters) for which the BIC is to be calculated.