BASHORATLI TAHLILLAR UCHUN MASHINALI O’QITISH ALGORITMLARI. QIYOSIY QARASHLAR

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Published Jan 28, 2023
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Vol. 2 No. 1 (2023): Journal of Integrated Education and Research

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Onarqulov Maqsad Karimberdiyevich
Farg’ona davlat universiteti f.m.f.b.f.d(PhD) o’qituvchisi
Yoqubjonov Alijon Mahamadamin o’g’li
Farg’ona davlat universiteti amaliy matematika yo’nalishi 2-kurs magistranti
Mahamadaminova Shahina Valijon qizi
Farg’ona davlat universiteti matematika fakulteti amaliy matematika yo’nalishi 3-kurs talabasi

Abstract

Ma'lumotlar to'plamining borgan sari oshib borishi va ular asosida kelajakda sodir bo’ladigan analitik jarayonlarni o’rganish insoniyatga juda katta foyda keltirayotganligi tufayli optimal bashoratli tahlillar mashhurlikka erishdi va bunda mashinali o’qitish algoritmi muhim ro’l kasb etgan. Ko'pgina bashorat qilish uchun yaratilgan mashinali o’qitish algoritmlari odatda bashoratli tahlil uchun qo'llaniladi, ammo bu ma'lumotlar to'plamidagi o'rganilayotgan muammo uchun to'g'ri algoritmni tanlash hali ham qiyin vazifadir. Ushbu maqola bashoratli tahlil uchun eng mashhur mashinali o’qitish algoritmlari va ularni ma'lumotlar to'plamida qo’llash natijalari tahlili haqida umumiy ma'lumot beradi. Ushbu algoritmlar ishlash vaqti, aniqlik, sezgirlik, o'ziga xoslik va xatolarga yo’l qo’yish kabi qiyosiy ishlash ko'rsatkichlari bilan baholanadi va tahlil qilinadi.

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How to Cite
Onarqulov Maqsad Karimberdiyevich, Yoqubjonov Alijon Mahamadamin o’g’li, & Mahamadaminova Shahina Valijon qizi. (2023). BASHORATLI TAHLILLAR UCHUN MASHINALI O’QITISH ALGORITMLARI. QIYOSIY QARASHLAR. Journal of Integrated Education and Research, 2(1), 130–134. Retrieved from https://ojs.rmasav.com/index.php/ojs/article/view/769

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