Development of innovative partially supervised machine learning algorithms

Abstract

The increasing number of technological products that interact with various views of a human’s life are currently characterized by a common factor: the production of vast amounts of data, compared especially to the corresponding quantities of the last decades. This fact, which has been ideally harmonized with the parallel evolvement of the storing systems and the data retrieval mechanisms, has inferred great obstacles during their exploitation as informative sources for training the corresponding learning models, according to the principles that are defined by the fields of Machine Learning and Data Mining. The main reason is the inability to obtain the ground truth of their target value, either in the case of Classification or Regression tasks, without procedures that demand a lot of time or monetization costs, regarding the large volumes of data that are usually available. As a solution to this reality, which is characterized by the existence of numerous unlabeled data along with only ...
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DOI
10.12681/eadd/47965
Handle URL
http://hdl.handle.net/10442/hedi/47965
ND
47965
Alternative title
Ανάπτυξη μερικώς επιβλεπόμενων αλγορίθμων μηχανικής μάθησης
Author
Karlos, Stamatis (Father's name: Georgios)
Date
2020
Degree Grantor
University of Patras
Committee members
Κωτσιαντής Σωτήριος
Καββαδίας Δημήτριος
Μουρτζόπουλος Ιωάννης
Βραχάτης Μιχαήλ
Χατζηλυγερούδης Ιωάννης
Σγάρμπας Κυριάκος
Καλλές Δημήτριος
Discipline
Natural Sciences
Computer and Information Sciences
Keywords
Machine learning; Partially supervised learning; Semi-supervised learning; Active learning; Wrapper methods; Labeled/Unlabeled data
Country
Greece
Language
Greek
Description
xviii, 414 σ., im., tbls., fig., ch.
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