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001-es BibID:	BIBFORM088787
035-os BibID:	(WoS)000600058700017 (Scopus)85098076385
Első szerző:	Tajti Tibor Gábor (informatikus)
Cím:	Fuzzification of training data class membership binary values for neural network algorithms / Tibor Tajti
Dátum:	2020
ISSN:	1787-5021 1787-6117
Megjegyzések:	We propose an algorithm improvement for classifying machine learning algorithms with the fuzzification of training data binary class membership values. This method can possibly be used to correct the training data out- put values during the training. The proposed modification can be used for algorithms running individual learners and also as an ensemble method for multiple learners for better performance. For this purpose, we define the single and the ensemble variants of the algorithm. Our experiment was done using convolutional neural network (CNN) classifiers for the base of our pro- posed method, however, these techniques might be used for other machine learning classifiers as well, which produce fuzzy output values. This fuzzi- fication starts with using the original binary class membership values given in the dataset. During training these values are modified with the current knowledge of the machine learning algorithm.
Tárgyszavak:	Természettudományok Matematika- és számítástudományok idegen nyelvű folyóiratközlemény hazai lapban folyóiratcikk machine learning neural networks fuzzification
Megjelenés:	Annales Mathematicae et Informaticae. - 52 (2020), p. 217-228. -
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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