KORXONA SAVDO HAJMINI BASHORATLASHDA MASHINALI OʻQITISH MODELLARINI ANIQLIK VA HISOBLASH SAMARADORLIGINI BAHOLASH
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Ushbu tadqiqotda oziq-ovqat distribyutor korxonasining 2026-yil yanvar-iyun oylariga oid 137 289 ta savdo kuzatuvi asosida kunlik sotuv miqdorini bashoratlash uchun oltita mashinali o‘qitish modeli qiyosiy baholandi. Modellar 12 ta kirish belgisi asosida vaqt bo‘yicha ajratilgan o‘qitish va test ma’lumotlarida MAE, RMSE, R², MAPE hamda o‘qitish vaqti bo‘yicha baholandi. Natijalarga ko‘ra, tasodifiy o‘rmon modeli R² = 0,518 qiymat bilan eng yuqori bashorat aniqligini ko‘rsatdi. Gistogrammaga asoslangan gradientli kuchaytirish (Histogram-based Gradient Boosting, HGB) modeli esa R² = 0,516 natijaga 1,43 sekundlik o‘qitish vaqti bilan erishdi. Olingan natijalar model samaradorligini baholashda bashorat aniqligi bilan birga o‘qitish vaqtini ham hisobga olish zarurligini ko‘rsatdi.
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