3 papers
cs.LG2026
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.LG2026
Cluster-Adaptive Feature Extraction and its Theoretical Foundation with Minkowski Weighted k-Means
Renato Cordeiro de Amorim, Vladimir Makarenkov
The Minkowski weighted -means (-means) algorithm extends classical -means by incorporating feature weights and a Minkowski distance. We first show that the -means o…
cs.LG2026
Improving clustering quality evaluation in noisy Gaussian mixtures
Renato Cordeiro de Amorim, Vladimir Makarenkov
Clustering is a well-established technique in machine learning and data analysis, widely used across various domains. Cluster validity indices, such as the Average Silhouette Width…