Final thesis deals with information-mining from large sets of medical data using methods and machine learning algorithms. The subject of the theoretical part is machine learning and its distribution, description of the basic data types in data mining, most important classifications and predictions methods, criterion defining the quality of prediction methods, description of data mining methodology and frequently used systems. The practical part focuses on statistical and informatics survey of provided medical data, appropriate transformation, subsequent design and implementation of experiments using machine learning methods to acquire new knowledge and hidden information and finally interpretation of the results together with conclusions for target groups.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:251164 |
| Date | January 2015 |
| Creators | Badelita, Elvyn-George |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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