Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/54E36216-1C8A-41C7-9848-DF38C838B0F4 | - |
| Identifier | https://doi.org/10.26233/heallink.tuc.95986 | - |
| Language | en | - |
| Extent | 70 pages | el |
| Extent | 3,7 megabytes | en |
| Title | Assessment metrics for clustering algorithms | en |
| Creator | Angelopoulos Vasileios | en |
| Creator | Αγγελοπουλος Βασιλειος | el |
| Contributor [Thesis Supervisor] | Matsatsinis Nikolaos | en |
| Contributor [Thesis Supervisor] | Ματσατσινης Νικολαος | el |
| Contributor [Committee Member] | Tsafarakis Stelios | en |
| Contributor [Committee Member] | Τσαφαρακης Στελιος | el |
| Contributor [Committee Member] | Grigoroudis Evangelos | en |
| Contributor [Committee Member] | Γρηγορουδης Ευαγγελος | el |
| Publisher | Πολυτεχνείο Κρήτης | el |
| Publisher | Technical University of Crete | en |
| Academic Unit | Πολυτεχνείο Κρήτης::Σχολή Μηχανικών Παραγωγής και Διοίκησης | el |
| Description | Master Thesis, Master of Technology and Innovation Management | en |
| Content Summary | In the first part of the Thesis, the theoretical background will be provided for Artificial Intelligence, Machine Learning, Supervised and Unsupervised Learning and Clustering in order to provide the basis for understanding the next chapters. In the second chapter, the theoretical and mathematical background is provided for each clustering algorithm that will be implemented. In the third chapter of the Thesis the different clustering assessment metrics are discussed and their mathematical background is presented. In the fourth chapter the basic steps of the implementation that will be carried out in order to provide the necessary outputs will be described. The intended output/result of the Thesis is the development of a software script in Python capable to take different datasets as an input, implement different clustering methods and export the clustering performance metrics. The correct operation of the developed script is shown in the final chapter where an example dataset is used to showcase the capabilities of the script by presenting the results/outputs of the script along with commentary. A manual covering the basic elements of the script can be found in the same chapter. | en |
| Type of Item | Μεταπτυχιακή Διατριβή | el |
| Type of Item | Master Thesis | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2023-05-25 | - |
| Date of Publication | 2023 | - |
| Subject | Clustering | en |
| Subject | Machine learning | en |
| Bibliographic Citation | Βασίλειος Αγγελόπουλος, "Assessment metrics for clustering algorithms", Μεταπτυχιακή Διατριβή, Σχολή Μηχανικών Παραγωγής και Διοίκησης, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2023 | el |
| Bibliographic Citation | Vasileios Angelopoulos, "Assessment metrics for clustering algorithms", Master Thesis, School of Production Engineering and Management, Technical University of Crete, Chania, Greece, 2023 | el |
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