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@inproceedings{44021, author = {Menšík, Marek and Duží, Marie and Albert, Adam and Patscka, Vojtěch and Pajr, Miroslav}, address = {Lappeenranta, Finland}, booktitle = {Frontiers in Artificial Intelligence and Applications}, doi = {http://dx.doi.org/10.3233/FAIA200024}, edition = {321}, editor = {Dhanayake, A.; Huiskonen, J.; Kiyoki, Y.; Thalheim, B.; Jaakkola, H.; Yoshida, N.}, keywords = {Generalization; Heuristics; Machine learning; Specialization; Transparent internsional logic; TIL; Hypothesis}, howpublished = {elektronická verze "online"}, language = {eng}, location = {Lappeenranta, Finland}, isbn = {978-1-64368-044-6}, pages = {344-362}, publisher = {IOS Press}, title = {Machine Learning Using TIL}, url = {http://ebooks.iospress.nl/publication/53709}, year = {2019} }
TY - JOUR ID - 44021 AU - Menšík, Marek - Duží, Marie - Albert, Adam - Patscka, Vojtěch - Pajr, Miroslav PY - 2019 TI - Machine Learning Using TIL PB - IOS Press CY - Lappeenranta, Finland SN - 9781643680446 KW - Generalization KW - Heuristics KW - Machine learning KW - Specialization KW - Transparent internsional logic KW - TIL KW - Hypothesis UR - http://ebooks.iospress.nl/publication/53709 L2 - http://ebooks.iospress.nl/publication/53709 N2 - In this paper we deal with machine learning methods and algorithms applied to the area of geographic data. First, we briefly introduce learning with a supervisor that is applied in our case. Then we describe the algorithm ‘Framework’ together with heuristic methods used in it. Definitions of particular geographic objects, i.e. their concepts, are formulated in our background theory Transparent Intensional Logic (TIL) as TIL constructions. These concepts serve as general hypotheses. Basic principles of supervised machine learning are generalization and specialization. Given a positive example, the learner generalizes, while after a near-miss example specialization is applied. Heuristic methods deal with the way generalization and specialization are applied. ER -
MENŠÍK, Marek, Marie DUŽÍ, Adam ALBERT, Vojtěch PATSCKA a Miroslav PAJR. Machine Learning Using TIL. Online. In Dhanayake, A.; Huiskonen, J.; Kiyoki, Y.; Thalheim, B.; Jaakkola, H.; Yoshida, N. \textit{Frontiers in Artificial Intelligence and Applications}. 321. vyd. Lappeenranta, Finland: IOS Press, 2019, s.~344-362. ISBN~978-1-64368-044-6. Dostupné z: https://dx.doi.org/10.3233/FAIA200024.
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