RANDOM FOREST ALGORITMI YORDAMIDA INTELLEKTUAL KLASSIFIKATSIYA MODELLARINI O‘QITISH VA METRIK TAHLIL
Keywords:
Random Forest, sun’iy intellekt, mashinali o‘rganish, ansambl metodlari, Python, Iris Dataset.Abstract
Mazkur tadqiqotda mashinali o‘rganish sohasidagi samarali ansambl metodlaridan biri – Random Forest algoritmining nazariy asoslari va amaliy qo‘llanilishi tahlil qilinadi. Model Python dasturlash tili hamda Scikit-learn kutubxonasi yordamida qurildi va Iris ma’lumotlar to‘plamida sinovdan o‘tkazildi. Tajriba natijalari Random Forest algoritmining yuqori aniqlik ko‘rsatkichlariga ega ekanligini hamda overfitting muammosiga nisbatan barqarorligini ko‘rsatdi. Model samaradorligi precision, recall, F1-score hamda belgilarning muhimlik darajasi orqali baholandi.
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