https://sloap.org/journal/index.php/ijecs <p><strong>IJECS </strong>is published in English and it is open to authors around the world regardless of the nationality. The issued frequency is annual or one issue per year publication.<br>ISSN 2632-945X</p> en-US <p>Articles published in the International Journal of Engineering &amp; Computer Science (<strong>IJECS</strong>) are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (<a href="https://creativecommons.org/licenses/by-nc-nd/4.0/" target="_blank" rel="noopener">CC BY-NC-ND 4.0</a>). Authors retain copyright in their work and grant <strong>IJECS&nbsp;</strong>right of first publication under CC BY-NC-ND 4.0. Users have the right to read, download, copy, distribute, print, search, or link to the full texts of articles in this journal, and to use them for any other lawful purpose.</p> <p>Articles published in <strong>IJECS</strong><strong>&nbsp;</strong>can be copied, communicated and shared in their published form for non-commercial purposes provided full attribution is given to the author and the journal. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (<em>e.g., post it to an institutional repository or publish it in a book</em>), with an acknowledgment of its initial publication in this journal.</p> editorsloap@gmail.com (Editorial Office) support@sloap.org (Vedran Vucic) Tue, 31 Dec 2024 00:00:00 +0000 OJS 3.2.1.1 http://blogs.law.harvard.edu/tech/rss 60 https://sloap.org/journal/index.php/ijecs/article/view/1782 <p>This article provides detailed information on machine learning processes, learning methods, supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, and the use of machine learning algorithms in the automatic extraction of metadata. Classification and regressive types of supervised learning, including decision trees, decision rules, Naive Bayes classifiers, Bayesian trust networks, nearest neighbor classifiers, linear discriminant functions, logistic regression, support vector machines, artificial neural networks, clustering and dimensionality reduction methods of unsupervised learning, semi-supervised learning, and reinforcement learning methods are also discussed.</p> Rashid Turgunbaev Copyright (c) 2024 International journal of engineering & computer science http://creativecommons.org/licenses/by-nc-nd/4.0 https://sloap.org/journal/index.php/ijecs/article/view/1782 Thu, 28 Mar 2024 00:00:00 +0000