MASHINAVIY O‘QITISHDA XUSUSIYATLAR TANLOVI VA O‘ZGARTIRISHNING AHAMIYATI
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xususiyatlar tanlovi, xususiyatlar o‘zgartirish, mashinaviy o‘qitish, ma'lumotlar tayyorlash, feature selection, feature engineering, model aniqligi, haddan tashqari moslashuv, normallashtirish, kategorik kodlash, ma'lumotlar sifati, umumlashtirish, hisoblash xarajatlari, interpretatsiya, yangi xususiyatlar yaratishAbstrak
Mashinaviy o‘qitish (machine learning) loyihalarida ma'lumotlarni tayyorlash bosqichi muvaffaqiyatning asosiy omillaridan biridir. Ushbu bosqichda xususiyatlar tanlovi (feature selection) va xususiyatlar o‘zgartirish (feature engineering) modelning samaradorligi, aniqligi va umumlashtirish qobiliyatiga katta ta'sir ko‘rsatadi. Ushbu maqolada ushbu jarayonlarning ahamiyati, afzalliklari va amaliy misollar keltiriladi.
Iqtiboslar
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Onlayn resurs: Scikit-learn Documentation. Feature Selection (https://scikit-learn.org/stable/modules/feature_selection.html).
Onlayn resurs: Kaggle Tutorials. Feature Engineering (https://www.kaggle.com/learn/feature-engineering).
Hall, M. A. (1999). Correlation-based Feature Selection for Machine Learning. Doctoral dissertation, University of Waikato.
