“MASHINALI O‘QITISHDA REGRESSIYA ENG KICHIK KVADRATLAR USULINI QO‘LLASH”
Keywords:
Eng kichik kvadratlar usuli, regressiya, chiziqli regressiya, mashinaviy o‘qitish, bashorat qilish, statistika, model aniqligi, ma’lumotlar tahliliAbstract
Regressiyada eng kichik kvadratlar usuli (Least Squares Method) — statistik analiz va mashinaviy o‘qitish sohasida keng qo‘llaniladigan asosiy metodlardan biridir. Bu usul yordamida bashorat qilinayotgan o‘zgaruvchilarga eng mos chiziqli model yaratilib, uning aniqligi oshiriladi. Ushbu maqolada regressiyaning eng kichik kvadratlar usulini qo‘llash, uning matematik asosi, ishlash prinsipi va amaliy misollar asosida tavsiflanadi. Shuningdek, usulning bashorat qilishda aniq va samarali natijalarga erishishga qanday hissa qo‘shishi va turli sharoitlarda uning ahamiyati muhokama qilinadi.
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References
Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd ed.). MIT Press.
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient Estimation of Word Representations in Vector Space. arXiv preprint arXiv:1301.3781.
Pedregosa, F., et al. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12, 2825-2830.
Kim, Y. (2014). Convolutional neural networks for sentence classification. arXiv preprint arXiv:1408.5882.
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805.
B.Umarov, M.Hakimov., “International journal of scientific researchers”, “Su’niy intelekt tizimlarida qayta tiklashga asoslangan o‘qitish” 2024y.
