{"id":9672969,"date":"2025-01-16T10:58:35","date_gmt":"2025-01-16T07:58:35","guid":{"rendered":"https:\/\/www.iee.ihu.gr\/?post_type=phd_students&#038;p=9672969"},"modified":"2025-07-04T14:24:24","modified_gmt":"2025-07-04T11:24:24","slug":"%ce%bc%cf%85%ce%bb%cf%89%ce%bd%ce%ac%cf%82-%ce%b9%cf%89%ce%ac%ce%bd%ce%bd%ce%b7%cf%82","status":"publish","type":"phd_students","link":"https:\/\/www.iee.ihu.gr\/en\/phd_students\/%ce%bc%cf%85%ce%bb%cf%89%ce%bd%ce%ac%cf%82-%ce%b9%cf%89%ce%ac%ce%bd%ce%bd%ce%b7%cf%82\/","title":{"rendered":"Mylonas Ioannis"},"content":{"rendered":"<p>The subject of the dissertation is the techniques for reducing training data (Data Reduction Techniques \u2013 DRTs) in classification problems. Specifically, these techniques, known as Prototype Selection (PS) algorithms and Prototype Generation algorithms, constitute a preprocessing step for training data with the aim of effective instance-based classification. Generally, these techniques are applied to training data that is organized in rows and columns and are capable of reducing the size of the data while maintaining high classification accuracy and reducing computational cost.<\/p>\n<p>The aim of the dissertation is to develop effective techniques for reducing complex training data, namely data related to data streams [1], distributed data [2],[3], data in non-metric spaces [4], data in complex structures (e.g., graphs), etc. Additionally, the development of data reduction techniques that take into account the phenomenon of concept drift [5] that appears in data streams is also a field of research. This phenomenon occurs when, over time, the distribution of data in space and classes changes.<\/p>\n<p><a name=\"_Toc179365160\"><\/a>\u0392\u03b9\u03b2\u03bb\u03b9\u03bf\u03b3\u03c1\u03b1\u03c6\u03b9\u03ba\u03ad\u03c2 \u0391\u03bd\u03b1\u03c6\u03bf\u03c1\u03ad\u03c2<\/p>\n<p>[1]\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u2018Streaming data\u2019, <em>Wikipedia<\/em>. 17 \u0391\u03cd\u03b3\u03bf\u03c5\u03c3\u03c4\u03bf\u03c2 2024. \u0397\u03bc\u03b5\u03c1\u03bf\u03bc\u03b7\u03bd\u03af\u03b1 \u03c0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7\u03c2: 9 \u039f\u03ba\u03c4\u03ce\u03b2\u03c1\u03b9\u03bf\u03c2 2024. [\u0388\u03ba\u03b4\u03bf\u03c3\u03b7 \u03c3\u03b5 \u03c8\u03b7\u03c6\u03b9\u03b1\u03ba\u03ae \u03bc\u03bf\u03c1\u03c6\u03ae]. \u0394\u03b9\u03b1\u03b8\u03ad\u03c3\u03b9\u03bc\u03bf \u03c3\u03c4\u03bf: https:\/\/en.wikipedia.org\/w\/index.php?title=Streaming_data&amp;oldid=1240848968<\/p>\n<p>[2]\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u2018Distributed database\u2019, <em>Wikipedia<\/em>. 31 \u0399\u03bf\u03cd\u03bb\u03b9\u03bf\u03c2 2024. \u0397\u03bc\u03b5\u03c1\u03bf\u03bc\u03b7\u03bd\u03af\u03b1 \u03c0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7\u03c2: 9 \u039f\u03ba\u03c4\u03ce\u03b2\u03c1\u03b9\u03bf\u03c2 2024. [\u0388\u03ba\u03b4\u03bf\u03c3\u03b7 \u03c3\u03b5 \u03c8\u03b7\u03c6\u03b9\u03b1\u03ba\u03ae \u03bc\u03bf\u03c1\u03c6\u03ae]. \u0394\u03b9\u03b1\u03b8\u03ad\u03c3\u03b9\u03bc\u03bf \u03c3\u03c4\u03bf: https:\/\/en.wikipedia.org\/w\/index.php?title=Distributed_database&amp;oldid=1237869130<\/p>\n<p>[3]\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 M. H. ur Rehman, C. S. Liew, A. Abbas, P. P. Jayaraman, T. Y. Wah, \u03ba\u03b1\u03b9 S. U. Khan, \u2018Big Data Reduction Methods: A Survey\u2019, <em>Data Sci. Eng.<\/em>, \u03c4. 1, \u03c4\u03c7. 4, \u03c3\u03b5\u03bb. 265\u2013284, \u0394\u03b5\u03ba\u03b5\u03bc\u03b2\u03c1\u03af\u03bf\u03c5 2016, doi: 10.1007\/s41019-016-0022-0.<\/p>\n<p>[4]\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u2018Hardware and Systems Engineering Design &#8211; Linear and Nonlinear Spaces\u2019. \u0397\u03bc\u03b5\u03c1\u03bf\u03bc\u03b7\u03bd\u03af\u03b1 \u03c0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7\u03c2: 30 \u03a3\u03b5\u03c0\u03c4\u03ad\u03bc\u03b2\u03c1\u03b9\u03bf\u03c2 2024. [\u0388\u03ba\u03b4\u03bf\u03c3\u03b7 \u03c3\u03b5 \u03c8\u03b7\u03c6\u03b9\u03b1\u03ba\u03ae \u03bc\u03bf\u03c1\u03c6\u03ae]. \u0394\u03b9\u03b1\u03b8\u03ad\u03c3\u03b9\u03bc\u03bf \u03c3\u03c4\u03bf: https:\/\/www.hwe.design\/theories-concepts\/foundation-of-the-study-of-linear-algebra-and-functional-analysis\/linear-and-nonlinear-spaces<\/p>\n<p>[5]\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 A. Liu, J. Lu, \u03ba\u03b1\u03b9 G. Zhang, \u2018Concept Drift Detection: Dealing With Missing Values via Fuzzy Distance Estimations\u2019, <em>IEEE Trans. Fuzzy Syst.<\/em>, \u03c4. 29, \u03c4\u03c7. 11, \u03c3\u03b5\u03bb. 3219\u20133233, \u0391\u03c5\u03b3\u03bf\u03cd\u03c3\u03c4\u03bf\u03c5 2021, doi: 10.1109\/TFUZZ.2020.3016040.<\/p>\n<p>&nbsp;<\/p>","protected":false},"featured_media":0,"template":"","meta":{"_acf_changed":false,"inline_featured_image":false},"class_list":["post-9672969","phd_students","type-phd_students","status-publish","hentry"],"acf":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.iee.ihu.gr\/en\/wp-json\/wp\/v2\/phd_students\/9672969","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.iee.ihu.gr\/en\/wp-json\/wp\/v2\/phd_students"}],"about":[{"href":"https:\/\/www.iee.ihu.gr\/en\/wp-json\/wp\/v2\/types\/phd_students"}],"wp:attachment":[{"href":"https:\/\/www.iee.ihu.gr\/en\/wp-json\/wp\/v2\/media?parent=9672969"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}