AUTOMATED MACHINE LEARNING YORDAMIDA AVTOMATIK MODEL TANLASH

Authors

  • Topivoldiyev Abbosbek Author

Keywords:

Kalit so‘zlar: AutoML, model tanlash, MO, giperparametr sozlash, meta- o‘qitish, Bayesian optimallashtirish, NAS, xususiyatlar muhandisligi, model baholash, oldindan qayta ishlash, SI.

Abstract

Annotatsiya: Ushbu maqola AutoML texnologiyalaridan foydalanib avtomatik 
model  tanlash  jarayonini  tahlil  qiladi.  An’anaviy  mashinaviy  o‘qitishda  ko‘p  vaqt 
oladigan  algoritm  tanlash  va  giperparametrlarni  sozlash  AutoML  yordamida 
avtomatlashtiriladi.  Tadqiqotda  AutoML  tizimlarining  ishlash  prinsiplari, 
optimallashtirish usullari va platformalarning samaradorligi ko‘rib chiqildi. Natijalar 
AutoML model ishlab chiqishni soddalashtirishi va yuqori aniqlikdagi modellarni tez 
yaratishga imkon berishini ko‘rsatdi. 

References

Foydalanilgan adabiyotlar

1. Hutter, F., Kotthoff, L., & Vanschoren, J. (2019). Automated Machine Learning:

Methods, Systems, Challenges. Springer.

2. Feurer, M., & Hutter, F. (2019). Hyperparameter Optimization. In Automated

Machine Learning (pp. 3–33). Springer.

3. Olson, R. S., & Moore, J. H. (2016). TPOT: A Tree-Based Pipeline Optimization

Tool for Automating Machine Learning. In Proceedings of the 2016 Python in

Science Conference.

4. He, X., Zhao, K., & Chu, X. (2021). AutoML: A Survey of the State-of-the-Art.

Knowledge-Based Systems.

5. Thornton, C., Hutter, F., Hoos, H. H., & Leyton-Brown, K. (2013). Auto-WEKA:

Combined Selection and Hyperparameter Optimization of Classification

Algorithms. In Proceedings of the 19th ACM SIGKDD International Conference on

Knowledge Discovery and Data Mining.

Published

2025-12-15

How to Cite

Topivoldiyev Abbosbek. (2025). AUTOMATED MACHINE LEARNING YORDAMIDA AVTOMATIK MODEL TANLASH . Ta’lim Innovatsiyasi Va Integratsiyasi, 59(2), 121-125. https://journalss.org/index.php/tal/article/view/10397