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001-es BibID:	BIBFORM103526
035-os BibID:	(Scopus)85107895755
Első szerző:	Szabó Máté (informatikus)
Cím:	Machine Learning on Android with Oracle Tribuo, SMILE and Weka / Máté Szabó
Dátum:	2021
Megjegyzések:	Machine learning is reaching nearly every programming language and most kinds of devices. While the most popular language for developing machine learning application is Python, it has its own limits, for example, the partial compatibility with Android devices. When a mobile application needs to train a model, it is easier to achieve this with the device`s native language like Java or Kotlin. There are many machine learning libraries for Java, but most of them lack Android support. This paper compares the resources needed to train random forest, support-vector machine and K-means models of the Weka, Tribuo and SMILE libraries. We developed an application to compare these libraries` implementations on datasets with various sizes. The results show that Weka is the suggested library for bigger datasets and complex models, as it is the least resource hungry
Tárgyszavak:	Műszaki tudományok Informatikai tudományok előadáskivonat könyvrészlet Android machine learning Tribuo SMILE mobile
Megjelenés:	Proceedings of the 1st Conference on Information Technology and Data Science / ed. István Fazekas, András Hajdu, Tibor Tómács. - p. 176-186. -
Pályázati támogatás:	EFOP-3.6.1-16-2016-00022 EFOP
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat
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