SUN’IY INTELLEKT TIZIMLARIDA GIPERPARAMETRLARNI MATEMATIK OPTIMALLASHTIRISH USULLARI
DOI:
https://doi.org/10.5281/zenodo.18985560Keywords:
sun’iy intellekt, giperparametr, matematik optimallashtirish, neyron tarmoq, mashinaviy o‘qitish, Bayes optimallashtirish, metaevristika, model aniqligiAbstract
Ushbu maqolada sun’iy intellekt tizimlarida giperparametrlarni matematik optimallashtirish usullari
o‘rganiladi. Tadqiqotda klassik yondashuvlar — qo‘lda sozlash, grid search va random search, shuningdek zamonaviy
yondashuvlar — Bayes optimallashtirish, metaevristik algoritmlar hamda adaptiv qidiruv strategiyalari qiyosiy tahlil qilinadi.
Giperparametrlarni to‘g‘ri tanlash modelning aniqligi, umumlashuv qobiliyati va hisoblash samaradorligiga sezilarli ta’sir
ko‘rsatishi asoslab beriladi. Maqolada ikki darajali matematik model taklif etilib, unda ichki qatlamda model parametrlari,
tashqi qatlamda esa giperparametrlar optimallashtirilishi ko‘rsatiladi.
References
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Das, D., Sadiq, A. S., Mirjalili, S. Optimization Algorithms in Machine Learning: A Meta-heuristics Perspective. –
Singapore: Springer, 2025.
Awasthi, M. K., Kumar, S., Saini, D. Artificial Intelligence Techniques in Mathematical Modeling and Optimization. –
London: Routledge, 2026.
Leon, F., Hulea, M., Gavrilescu, M. Advances in Artificial Intelligence: Models, Optimization and Machine Learning. –
Mathematics, MDPI Journal, 2022.
Yang, L., Shami, A. On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice. – arXiv
preprint, 2020.
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