Comparative analysis of modified semi-supervised learning algorithms on a small amount of labeled data

The paper is devoted to improving semi-supervised clustering methods and comparing their accuracy and robustness. The proposed approach is based on expanding a clustering algorithm for using an available set of labels by replacing the distance function. Using the distance function considers not onl...

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Autors principals:	Leonid Lyubchyk, Klym Yamkovyi
Format:	Artigo
Idioma:	Ucraniano
Publicat:	Igor Sikorsky Kyiv Polytechnic Institute 2022-12-01
Col·lecció:	Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï
Matèries:	center of mass clustering distance function medoids nearest neighbor semi-supervised learning
Accés en línia:	http://journal.iasa.kpi.ua/article/view/239726
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