ELEKTRON TA’LIM TIZIMIDA TALABA BILIMINI BAHOLASH UCHUN KLASTERLASH ALGORITMI: K YAQIN QO‘SHNI (KNN) ALGORITMIDAN FOYDALANISH.
Keywords:
Klasterlash, Evklid algoritmi, Xemming algoritmi, nominal attribut, numerik attribut.Abstract
Bugungi IT sohasi rivojlanib borayotgan davrda elektron ta’lim hamda unda talabalar bilimini baholash masalasi davr talabi sanaladi. Talaba bilimini baholashda ma’lumotlarni intellektli tahlil qilish ham dolzarb masaladir. Intellektli tahlil jarayon algoritmlari, ma’lumotlar ham holisona baholashga xizmat ko‘rsatmog‘i kerak. Ushbu maqolada talaba bilimini baholashda muhim o‘rin tutadigan barcha attributlar va ularning qiymatlari e’tiborga olindi. Tuzilgan data set yordamida K yaqin qo‘shni algoritmi asosida hisoblashlar amalga oshirildi. Talaba bilimini baholashda ushbu algoritmning afzallik hamda kamchilik jihatlari keltirib o‘tildi.
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