Keywords
Abstract
Ushbu maqolada axborot tizimlarida uchraydigan yetishmayotgan (NaN) qiymatlarni aniqlash va ularni to‘ldirishga oid nazariy yondashuvlar chuqur tahlil qilinadi.
Ma’lumotlar to‘plamining sifati intellektual tahlil jarayonlarining ishonchliligi va samaradorligiga bevosita ta’sir ko‘rsatadi. Shu bois, NaN qiymatlarni bartaraf etish algoritmlari hozirgi davr axborot texnologiyalarida dolzarb masala sifatida namoyon bo‘lmoqda. Maqolada 7 ta asosiy metod – o‘rtacha qiymat, median, moda, regressiya, K eng yaqin qo‘shni (KNN), interpolatsiya va sun’iy neyron tarmoqlar yordamida to‘ldirish – nazariy jihatdan o‘rganildi. Har bir metod hisoblash murakkabligi, dispersiyaga ta’siri, modelga sezgirlik darajasi, bashorat aniqligi va ma’lumotlar tiplariga nisbatan moslashuvchanlik mezonlari bo‘yicha baholandi. Tadqiqotda metodlarning kuchli va zaif jihatlari asoslangan holda tahlil qilinib, turli kontekstlar uchun optimal yondashuvni tanlash zarurati asoslab berildi. Shuningdek, kombinatsiyalangan (hibrid) algoritmlar yordamida kompleks yondashuvlar ishlab chiqish istiqbollari ham ilgari surildi. Ushbu maqola axborot tizimlarida intellektual tahlil sifatini oshirish, sun’iy intellekt modellarining aniqligini ta’minlash hamda raqamli transformatsiya jarayonlarini samarali tashkil etish uchun muhim nazariy asos bo‘lib xizmat qiladi.
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