conference paper · Chinese Control Conference (CCC) · 2020
Automated data cleaning for data centers: A case study
Syed Naeem Haider, Qianchuan Zhao, Bushra Kainat Meran
Cited by 7Abstract and details only
Abstract
Preprocessing the raw data is a critical stage in machine learning whose fundamental objective is to prepare a cleaned and error-free data set for data analytic algorithms. Transforming raw data into clean data is a basic requirement in industrial and commercial sectors but there are many challenges which have to be addressed individually and manually. Since there is no unified framework that incorporates all the required fields to transform raw data into clean data, manual transformation is ineffective and very time consuming. We discuss a case study for cleaning data in data center, comparing missing values filling issue with forecast and mean value replacement for missing values and propose an automated data preprocessing framework for data cleaning. Proposed frame work successfully cleans data sets automatically instead of dealing multiple problems distinctly and manually.
Cite this paper
Haider, S. N., Zhao, Q., & Meran, B. K. (2020). Automated data cleaning for data centers: A case study. Chinese Control Conference (CCC), 3227–3232. https://doi.org/10.23919/ccc50068.2020.9189357
Haider, Syed Naeem, et al. “Automated data cleaning for data centers: A case study.” Chinese Control Conference (CCC), 2020, pp. 3227–32, https://doi.org/10.23919/ccc50068.2020.9189357.
Haider, Syed Naeem, Qianchuan Zhao, and Bushra Kainat Meran. 2020. “Automated data cleaning for data centers: A case study.” Chinese Control Conference (CCC): 3227–32. https://doi.org/10.23919/ccc50068.2020.9189357.
Haider, S.N., Zhao, Q. and Meran, B.K. (2020) ‘Automated data cleaning for data centers: A case study’, Chinese Control Conference (CCC), pp. 3227–3232. Available at: https://doi.org/10.23919/ccc50068.2020.9189357.
@article{haider2020automated,
title = {{Automated data cleaning for data centers: A case study}},
author = {Haider, Syed Naeem and Zhao, Qianchuan and Meran, Bushra Kainat},
journal = {Chinese Control Conference (CCC)},
pages = {3227--3232},
year = {2020},
doi = {10.23919/ccc50068.2020.9189357}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.
Related papers
Automated Data Cleansing through Meta-Learning
Ian Gemp, Georgios Theocharous, Mohammad Ghavamzadeh · Proceedings of the AAAI Conference on Artificial Intelligence · 2017
Cited by 17Open access
Automated data preprocessing and training interface for machine learning applications
Anagha Challa, Akhila Vutukuri, Maithreyi Kenguva et al. · AIP conference proceedings · 2024
Cited by 3
A Survey on Data Cleaning Methods for Improved Machine Learning Model Performance
Ga Young Lee, Lubna Alzamil, Bakhtiyar Doskenov et al. · arXiv (Cornell University) · 2021
Cited by 71Open access
Automated Data Cleaning and Preprocessing System
Aman Rawat, Mr.Ritesh Kumar · Zenodo (CERN European Organization for Nuclear Research) · 2025
Cited by 0Open access
A Multi-purpose Data Pre-processing Framework using Machine Learning for Enterprise Data Models
Venkata Ramana B, G. Narsimha · International Journal of Advanced Computer Science and Applications · 2021
Cited by 2Open access
DATA CLEANING AND PREPROCESSING AUTOMATION IN PYTHON: AN EFFICIENT PIPELINE APPROACH
Y. Suresh Babu, K. Vijayakumar · International Journal of Engineering Research and Science & Technology · 2025
Cited by 0Open access