3 papers
cs.LG2025
ClustRecNet: A Novel End-to-End Deep Learning Framework for Clustering Algorithm Recommendation
Mohammadreza Bakhtyari, Bogdan Mazoure, Renato Cordeiro de Amorim +2
Identifying an effective clustering algorithm for a given dataset remains a fundamental unsupervised learning issue. We introduce ClustRecNet, a novel end-to-end deep learning fram…
cs.LG2018
An efficient density-based clustering algorithm using reverse nearest neighbour
Stiphen Chowdhury, Renato Cordeiro de Amorim
Density-based clustering is the task of discovering high-density regions of entities (clusters) that are separated from each other by contiguous regions of low-density. DBSCAN is,…
stat.ML2016
Recovering the number of clusters in data sets with noise features using feature rescaling factors
Renato Cordeiro de Amorim, Christian Hennig
In this paper we introduce three methods for re-scaling data sets aiming at improving the likelihood of clustering validity indexes to return the true number of spherical Gaussian…