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

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 only...

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Bibliographic Details
Main Authors: Leonid Lyubchyk, Klym Yamkovyi
Format: Article
Language:Ukrainian
Published: Igor Sikorsky Kyiv Polytechnic Institute 2022-12-01
Series:Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï
Subjects:
center of mass
clustering
distance function
medoids
nearest neighbor
semi-supervised learning
Online Access:http://journal.iasa.kpi.ua/article/view/239726

Internet

http://journal.iasa.kpi.ua/article/view/239726

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