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A Model-Based Clustering Approach for Bounded Data Using Transformation-Based Gaussian Mixture Models
Luca Scrucca
The clustering of bounded data presents unique challenges in statistical analysis due to the constraints imposed on the data values. This paper introduces a novel method for model-…
A Model-Based Approach to Shot Charts Estimation in Basketball
Luca Scrucca, Dimitris Karlis
Shot charts in basketball analytics provide an indispensable tool for evaluating players' shooting performance by visually representing the distribution of field goal attempts acro…
Assessing uncertainty in Gaussian mixtures-based entropy estimation
Luca Scrucca
Entropy estimation plays a crucial role in various fields, such as information theory, statistical data science, and machine learning. However, traditional entropy estimation metho…
An introduction and tutorial to model-based clustering in education via Gaussian mixture modelling
Luca Scrucca, Mohammed Saqr, Sonsoles López-Pernas +1
Heterogeneity has been a hot topic in recent educational literature. Several calls have been voiced to adopt methods that capture different patterns or subgroups within students be…
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…
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…