QARORLAR DARAXTI ALGORITMINING SUN'IY INTELLEKTDAGI AMALIY TADBIQLARI
Keywords:
Qarorlar daraxti, sun'iy intellekt, tibbiyotda qo'llanilishi, moliyaviy sohada qo'llanilishi, marketing, mashinasozlik, qishloq xo'jaligi, ortiqcha moslashish, ma'lumot ifloslanishi, amaliy tadbiqlar.Abstract
Ushbu maqolada qarorlar daraxti algoritmining turli sohalardagi amaliy tadbiqlari ko'rib chiqiladi. Qarorlar daraxti sun'iy intellektning muhim vositalaridan biri bo'lib, uning asosiy tuzilishi va ishlash printsipi haqida ma'lumotlar beriladi. Tibbiyot, moliya, marketing, mashinasozlik va qishloq xo'jaligi kabi sohalarda qarorlar daraxti modeli qanday ishlatilishi va uning afzalliklari yoritiladi. Shuningdek, qarorlar daraxtining kamchiliklari va ularni bartaraf etish usullari ham ko'rib chiqiladi. Kelajakda qarorlar daraxtining rivojlanish yo'nalishlari va yangi amaliy tadbiqlar uchun imkoniyatlar ham muhokama qilinadi. Maqola sun'iy intellekt texnologiyalari bilan qiziqqan mutaxassislar va tadqiqotchilar uchun foydali bo'lishi kutiladi.
References
Quinlan, J. R. (1986). "Induction of Decision Trees". Machine Learning. Springer.
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). "Classification and Regression Trees". Wadsworth.
Quinlan, J. R. (1993). "C4.5: Programs for Machine Learning". Morgan Kaufmann.
Hastie, T., Tibshirani, R., & Friedman, J. (2009). "The Elements of Statistical Learning: Data Mining, Inference, and Prediction". Springer.
Mitchell, T. M. (1997). "Machine Learning". McGraw Hill.
Rokach, L., & Maimon, O. (2014). "Data Mining with Decision Trees: Theory and Applications". World Scientific.
Murthy, S. K. (1998). "Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey". Data Mining and Knowledge Discovery.
Witten, I. H., Frank, E., & Hall, M. A. (2011). "Data Mining: Practical Machine Learning Tools and Techniques". Morgan Kaufmann.
Han, J., Kamber, M., & Pei, J. (2012). "Data Mining: Concepts and Techniques". Morgan Kaufmann.
Larose, D. T. (2005). "Discovering Knowledge in Data: An Introduction to Data Mining". Wiley-Interscience.
Provost, F., & Fawcett, T. (2013). "Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking". O'Reilly Media.
Tsoumakas, G., & Katakis, I. (2007). "Multi-label Classification: An Overview". International Journal of Data Warehousing and Mining.
Domingos, P. (2015). "The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World". Basic Books.
Elkan, C. (2001). "The Foundations of Cost-Sensitive Learning". Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence.
Kotsiantis, S. B. (2013). "Decision Trees: A Recent Overview". Artificial Intelligence Review.
Tojimamatov, I. N., Olimov, A. F., Khaydarova, O. T., & Tojiboyev, M. M. (2023). CREATING A DATA SCIENCE ROADMAP AND ANALYSIS. PEDAGOGICAL SCIENCES AND TEACHING METHODS, 2(23), 242-250.
Тожимаматов, И. Н. (2023). ЗАДАЧИ ИНТЕЛЛЕКТУАЛЬНОГО АНАЛИЗА ДАННЫХ. PEDAGOG, 6(4), 514-516.
Muqaddam, A., Shahzoda, A., Gulasal, T., & Isroil, T. (2023). NEYRON TARMOQLARDAN FOYDALANIB TASVIRLARNI ANIQLASH USULLARI. SUSTAINABILITY OF EDUCATION, SOCIO-ECONOMIC SCIENCE THEORY, 1(8), 63-74.
Raximov, Q. O., Tojimamatov, I. N., & Xo, H. R. O. G. L. (2023). SUNIY NЕYRON TARMOQLARNI UMUMIY TASNIFI. Scientific progress, 4(5), 99-107.
Ortiqovich, Q. R., & Nurmamatovich, T. I. (2023). NEYRON TARMOQNI O ‘QITISH USULLARI VA ALGORITMLARI. Scientific Impulse, 1(10), 37-46.
Tojimamatov, I. N., Mamalatipov, O., Rahmatjonov, M., & Farhodjonov, S. (2023). NEYRON TARMOQLAR. Наука и инновация, 1(1), 4-12.
Tojimamatov, I. N., Mamalatipov, O. M., & Karimova, N. A. (2022). SUN’IY NEYRON TARMOQLARINI O ‘QITISH USULLARI. Oriental renaissance: Innovative, educational, natural and social sciences, 2(12), 191-203.
Muqaddam, A., Shahzoda, A., Gulasal, T., & Isroil, T. (2023). NEYRON TARMOQLARDAN FOYDALANIB TASVIRLARNI ANIQLASH USULLARI. SUSTAINABILITY OF EDUCATION, SOCIO-ECONOMIC SCIENCE THEORY, 1(8), 63-74.
Raximov, Q. O., Tojimamatov, I. N., & Xo, H. R. O. G. L. (2023). SUNIY NЕYRON TARMOQLARNI UMUMIY TASNIFI. Scientific progress, 4(5), 99-107.
Raxmatjonova, M. N., & Tojimamatov, I. N. (2023). BIZNESDA SUNIY INTELEKT TEXNOLOGYALARI VA ULARNI AHAMIYATI. Лучшие интеллектуальные исследования, 11(3), 46-52.
Nurmatovich, T. I. (2024). Bir qatlamli va ko ‘p qatlamli neyron to ‘rlari. ILM FAN XABARNOMASI, 1(1), 190-191.
Nurmamatovich, T. I., & Kudratullo o‘g, K. U. B. (2024). THE EVOLUTION OF AI: FROM EARLY CONCEPTS TO MODERN BREAKTHROUGHS. Лучшие интеллектуальные исследования, 20(2), 42-46.
Tojimamatov, I., & G’ulomjonova, S. (2024). NEYRO KOMPYUTERLAR VA ULARNING ARXITEKTURASI. Development of pedagogical technologies in modern sciences, 3(6), 10-16.
Tojimamatov, I., & Jo’rayeva, M. (2024). BOLSMAN MASHINASI VA UNING AHAMIYATI. Development and innovations in science, 3(4), 154-160.
Nurmamatovich, T. I., & Nozimaxon, E. (2024). Chiqish qatlami vaznlarni sozlash va xatoliklarni teskari tarqalishi algoritmi. ILM FAN XABARNOMASI, 1(1), 29-35.
Tojimamatov, I., & Ismoiljonova, O. (2024). BIR QATLAMLI PERCEPTRONNI O ‘QITISH. Академические исследования в современной науке, 3(12), 153-158.
Nurmamatovich, T. I. (2024, April). BIR QATLAMLI PERCEPTRONNI O ‘QITISH. In " CANADA" INTERNATİONAL CONFERENCE ON DEVELOPMENTS İN EDUCATİON, SCİENCESAND HUMANİTİES (Vol. 17, No. 1).
Nurmamatovich, T. I. (2024, April). SUN'IY NEYRONNING MATEMATIK MODELI HAMDA FAOLLASHTIRISH FUNKTSIYALARI. In " USA" INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE TOPICAL ISSUES OF SCIENCE (Vol. 17, No. 1).
Nurmamatovich, T. I. (2024, April). SUNIY NEYRON TORLARINI ADAPTIV KUCHAYTIRISH USULI. In " USA" INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE TOPICAL ISSUES OF SCIENCE (Vol. 17, No. 1).
Nurmamatovich, T. I. (2024). XEBB O’QITISH QOIDASI. " GERMANY" MODERN SCIENTIFIC RESEARCH: ACHIEVEMENTS, INNOVATIONS AND DEVELOPMENT PROSPECTS, 17(1).
Tojimamatov, I., & G’ulomjonova, S. (2024). NEYRO KOMPYUTERLAR VA ULARNING ARXITEKTURASI. Development of pedagogical technologies in modern sciences, 3(6), 10-16.
