1 citations · 1 across the 2 of their papers we have counts for
5 papers
Modal clustering on PPGMMGA projection subspace
Luca Scrucca
PPGMMGA is a Projection Pursuit (PP) algorithm aimed at detecting and visualizing clustering structures in multivariate data. The algorithm uses the negentropy as PP index obtained…
Handling missing data in model-based clustering
Alessio Serafini, Thomas Brendan Murphy, Luca Scrucca
Gaussian Mixture models (GMMs) are a powerful tool for clustering, classification and density estimation when clustering structures are embedded in the data. The presence of missin…
Projection pursuit based on Gaussian mixtures and evolutionary algorithms
Luca Scrucca, Alessio Serafini
We propose a projection pursuit (PP) algorithm based on Gaussian mixture models (GMMs). The negentropy obtained from a multivariate density estimated by GMMs is adopted as the PP i…
Better than the best? Answers via model ensemble in density-based clustering
Alessandro Casa, Luca Scrucca, Giovanna Menardi
With the recent growth in data availability and complexity, and the associated outburst of elaborate modelling approaches, model selection tools have become a lifeline, providing o…
A transformation-based approach to Gaussian mixture density estimation for bounded data
Luca Scrucca
Finite mixture of Gaussian distributions provide a flexible semi-parametric methodology for density estimation when the variables under investigation have no boundaries. However, i…