A new ensemble self-labeled semi-supervised algorithm

Ioannis E. Livieris
2019 Informatica (Ljubljana, Tiskana izd.)  
As an alternative to traditional classification methods, semi-supervised learning algorithms have become a hot topic of significant research, exploiting the knowledge hidden in the unlabeled data for building powerful and effective classifiers. In this work, a new ensemble-based semi-supervised algorithm is proposed which is based on a maximum-probability voting scheme. The reported numerical results illustrate the efficacy of the proposed algorithm outperforming classical semi-supervised
more » ... thms in term of classification accuracy, leading to more efficient and robust predictive models. Povzetek: Razvit je nov delno nadzorovani učni algoritem s pomočjo ansamblov in glasovalno shemo na osnovi največje verjetnosti.
doi:10.31449/inf.v43i2.2217 fatcat:skxctlhzwjhzrooprj7qxxnaxu