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comparison-of-open-source-data-mining-tools-naive-bayes-algorith-2019


Scalable and Secure Big Data I
Abstract


Veri Madencili─?i, b├╝y├╝k verilerin analiz edilme a┼?amas─▒nda bir├žok disiplini bir arada kullanan i┼?lemler b├╝t├╝n├╝d├╝r. Bilgisayar teknolojileri, istatistiksel analiz teknikleri, veritaban─▒ teknolojileri ve bir├žok disiplinleri bir araya getiren veri madencili─?i kavram─▒d─▒r. Veri Madencili─?i uygulamalar─▒n─▒ ger├žekle┼?tirmek i├žin ticari ve a├ž─▒k kaynak olmak ├╝zere bir├žok program mevcuttur. Bu ├žal─▒┼?mada a├ž─▒k kaynak kodlu Veri Madencili─?i programlar─▒ndan olan WEKA, Orange, Knime ile anlat─▒lm─▒┼? olup, bu programlar─▒n hepsinde yer alan S─▒n─▒fland─▒rma algoritmas─▒ ile bir ├Ârnek ├ž├Âz├╝mlenmi┼?tir. Bu ├žal─▒┼?mada UCI Machine Learning Repository veritaban─▒ndan Ô??iris, breast cancer, wine, monk, balanceÔ?? veri setleri al─▒narak Naive Bayes s─▒n─▒fland─▒rma algoritmas─▒yla bu 3 a├ž─▒k kaynak kodlu Veri Madencili─?i programlar─▒ aras─▒ndaki fark─▒n ortaya ├ž─▒kar─▒lmas─▒ hedeflenmi┼?tir. Ger├žekle┼?tirilen bu ├žal─▒┼?ma ile programlardan al─▒nan ├ž─▒kt─▒lara g├Âre kar┼?─▒la┼?t─▒rma yapmaya y├Ânelik ├Âneriler yer almaktad─▒r.

KeyWords
Veri Madencili─?i, S─▒n─▒fland─▒rma Analizi, Naive Bayes



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