ANSAMBL USULLARIDAN FOYDALANIB KO‘KRAK BEZI SARATONINI TASHXISLASHNING SAMARADORLIGINI BAHOLASH

Dildora Muhamediyeva; Madina Shoazizova; Zilola Saidova

Authors

Dildora Muhamediyeva Muhammad al-Xorazmiy nomidagi Toshkent axborot texnologiyalari universiteti
Madina Shoazizova Muhammad al-Xorazmiy nomidagi Toshkent axborot texnologiyalari universiteti
Zilola Saidova Muhammad al-Xorazmiy nomidagi Toshkent axborot texnologiyalari universiteti

Keywords:

Ko‘krak bezi saratoni, ansambl usullari, mashinaviy o‘qitish, Random Forest, Gradient Boosting, AdaBoost, Bagging, Model Stacking, AUC-ROC, tibbiy tashxis

Abstract

Mazkur maqolada ko‘krak bezi saratonini tashxislashda qo‘llaniladigan ansambl mashinaviy o‘qitish usullarining samaradorligi ilmiy jihatdan tahlil qilinadi. Tadqiqot doirasida Random Forest, Gradient Boosting, Bagging, AdaBoost va Model Stacking algoritmlaridan foydalanildi hamda ularning aniqlik, aniqlik darajasi, eslab qolish, F1-mezon va AUC-ROC kabi ko‘rsatkichlari taqqoslab o‘rganildi. Tahlil natijalari Model Stacking yondashuvi umumiy aniqlik va muvozanatli ko‘rsatkichlar bo‘yicha yuqori samaradorlik namoyon etganini ko‘rsatadi. Shu bilan birga, Random Forest algoritmi sinflarni ajratish qobiliyati jihatidan afzalliklarga ega ekani aniqlandi. Ushbu izlanishlar ansambl usullarining tibbiy tashxislashda qo‘llanish imkoniyatlarini kengaytirishini hamda klinik qarorlarni qo‘llab-quvvatlash tizimlarida samarali integratsiya qilinishi mumkinligini asoslab beradi.

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