Sun’iy intellekt modelini qurishda ma’lumotlarni tozalash bosqichi tahlili
Sun’iy intellekt modelini qurishda ma’lumotlarni tozalash bosqichi tahlili
Abstract
Annotatsiya. Ma‘lumki bugungi kunda ko‗plab muammolarning eng optimal yechimi sifatida qaralayotgan sun‘iy intellekt texnologiyalari ma‘lumotlarga asoslanadi. Boshqacha so‗z bilan aytganda, sun‘iy intellekt texnologiyalari beradigan qarorlarning aniqliligi o‗quv ma‘lumotlari sifatiga bog‗liq. Haqiqiy dunyoda ma‘lumotlar to‗plami odatda o‗zida turli anomoliyalarni saqlashi mumkin. Shuning uchun sun‘iy intellekt algoritmlaridan foydalanishdan oldin ma‘lumotlar ustida bajariladigan muhim amallardan biri bu ma‘lumotlarni tozalash bosqichlaridir. Ushbu maqolada ma‘lumotlarni tozalash jarayoni tahlili keltirilgan bo‗lib, ma‘lumotlarni tozalash jarayonida nimalarga e‘tibor berilishi lozimligi haqida firk mulohazalar yuritiladi.
References
Chapman, A. D. 2005. ―Principles and Methods of Data Cleaning – Primary Species and Species Occurrence Data‖, Report for the Global Biodiversity Information Facility, Copenhagen
Rashidov, A., Akhatov, A., Nazarov, F. (2023). The Same Size Distribution of Data Based on Unsupervised Clustering Algorithms. In: Hu, Z., Zhang, Q., He, M. (eds) Advances in Artificial Systems for Logistics Engineering III. ICAILE 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 180. Springer, https://doi.org/10.1007/978-3-031-36115-9_40
Akhatov A., Renavikar A., Rashidov A., Nazarov F. ―Optimization of the number of databases in the Big Data processing‖ Проблемы информатики, № 1(58) 2023, DOI: 10.24412/2073-0667-2023-1-33-47
Rashidov A.E., Sayfullaev J.S. ―Selecting methods of significant data from gathered datasets for research‖ International journal of advanced research in education, technology and management, Volume 3, Issue 2, 2024/2/26, P. 289-296
Akhatov A., Renavikar A., Rashidov A. ―Optimization of the database structure based on Machine Learning algorithms in case of increased data flow‖ Proceedings of the International Conference on Artificial Intelligence, Blockchain, Computing And Security (ICABCS 2023), Gr. Noida, Up, India, 24-25 February 2023
Rashidov, A., Akhatov, A. R., & Nazarov, F. M. (2023). Real-Time Big Data Processing Based on a Distributed Computing Mechanism in a Single Server. In C. Ananth, N. Anbazhagan, & M. Goh (Eds.), Stochastic Processes and Their Applications in Artificial Intelligence (pp. 121-138). IGI Global. https://doi.org/10.4018/978-1-6684-7679-6.ch009
Guide To Data Cleaning: Definition, Benefits, Components, And How To Clean Your Data, from https://www.tableau.com/learn/articles/what-is-data-cleaning
Fakhitah R., Wan M.N., Wan Z. ―A Review on Data Cleansing Methods for Big Data‖ The Fifth Information Systems International Conference 2019, P. 731–738
Jon Kowieski ―Data cleaning: What it is, examples, and how to keep your data clean in 7 steps‖ Published Dec 2, 2022
Rashidov A., Akhatov A., Aminov A, and Mardonov D. ―Distribution of data flows in distributed systems using hierarchical clustering,‖ International conference on Artificial Intelligence and Information Technologies (ICAIIT 2023), Uzbekistan, Samarkand, 2023
Rashidov A., Akhatov A., and Mardonov D. ―The Distribution algorithm of Data Flows Based on the BIRCH Clustering in the Internal Distribution Mechanism‖ 2023 International Russian Smart Industry Conference, SmartIndustryCon 2023, 2023
Craig Stedman ―Data cleansing (data cleaning, data scrubbing)‖ https://www.techtarget.com/searchdatamanagement/definition/data-scrubbing
Akhatov A., Renavikar A., Rashidov A. & Nazarov F. ―Development of the Big Data processing architecture based on distributed computing systems‖ Informatika va energetika muammolari O‗zbekiston jurnali, № (1) 2022, 71-79
Akhatov A. & Rashidov A. ―Big Data va unig turli sohalardagi tadbiqi‖, Descendants of Muhammad Al-Khwarizmi, 2021, № 4 (18), 135-44