3 papers
cs.AI2025
A Neuro-Fuzzy System for Interpretable Long-Term Stock Market Forecasting
Miha Ožbot, Igor Škrjanc, Vitomir Štruc
In the complex landscape of multivariate time series forecasting, achieving both accuracy and interpretability remains a significant challenge. This paper introduces the Fuzzy Tran…
cs.LG2025
Measures of Overlapping Multivariate Gaussian Clusters in Unsupervised Online Learning
Miha Ožbot, Igor Škrjanc
In this paper, we propose a new measure for detecting overlap in multivariate Gaussian clusters. The aim of online learning from data streams is to create clustering, classificatio…
cs.LG2025
Federated Learning based on Self-Evolving Gaussian Clustering
Miha Ožbot, Igor Škrjanc
In this study, we present an Evolving Fuzzy System within the context of Federated Learning, which adapts dynamically with the addition of new clusters and therefore does not requi…