Subject: machine learning algorithms, numeric datasets, k-nearest neighbor graph
Year: 2023
Type: Proceeding article
Title: Performance Analysis of Machine Learning Algorithms on Small Datasets that Includes Features from K-Nearest Neighbor Graph
Author: Ilievska, Elena
Author: Sekuloski, Petar
Abstract: Modern technology in today’s world is largely driven by machine learning algorithms. They are incorporated into every field. Big data is not always available to us, though. We frequently have to work with limited-size of data. The purpose of this paper is to demonstrate several machine learning algorithms and their accuracy on small numerical datasets. We investigate the effectiveness of these algorithms with and without the implementation of two variables, degree and closeness centrality, which are extracted from the dataset using the knearest neighbor graph.
Publisher: Ss Cyril and Methodius University in Skopje, Faculty of Computer Science and Engineering, Republic of North Macedonia
Relation: CIIT 2023 papers;34;
Identifier: oai:repository.ukim.mk:20.500.12188/27409
Identifier: http://hdl.handle.net/20.500.12188/27409
