Fault diagnosis for a milk pasteurisation plant with missing data

Kadri, Ouahab; Mouss, Leïla Hayet; Abdelhadi, Adel

doi:10.1504/ijqet.2017.088858

Cited by 1 publication

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“…The larger the difference between them, the higher the variance of errors in the dataset. Next is the execution time, which varies among studies based on the size of the dataset, missing values, and computational resources used to conduct the experiment [74]. Huang et al [87] indicated that the complication in their proposed method causes a significant increase in execution time for the algorithm.…”

Section: Rq4 What Are the Measurement Factors Used To Evaluate The Ml...mentioning

confidence: 99%

Systematic Review of Using Machine Learning in Imputing Missing Values

et al. 2022

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Missing data are a universal data quality problem in many domains, leading to misleading analysis and inaccurate decisions. Much research has been done to investigate the different mechanisms of missing data and the proper techniques in handling various data types. In the last decade, machine learning has been utilized to replace conventional methods to address the problem of missing values more efficiently. By studying and analyzing recently proposed methods using machine learning approaches, vital adoptions in accuracy, performance, and time consumed can be highlighted. This study aimed to help data analysts and researchers address the limitations of machine learning imputation methods by conducting a systematic literature review to provide a comprehensive overview of using such methods to impute missing values. Novel proposed machine learning approaches used for data imputation are analyzed and summarized to assist researchers in selecting a proper machine learning method based on several factors and settings. The review was performed on research studies published between 2016 and 2021 on adopting machine learning to impute missing values, focusing on their strengths and limitations. A total of 684 research articles from various scientific databases were analyzed using search engines, and 94 of them were selected as primary studies. Finally, several recommendations were given to guide future researchers in applying machine learning to impute missing values.INDEX TERMS Systematic literature review, data imputation, data mining, missingness, data preprocessing, data quality.

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Section: Rq4 What Are the Measurement Factors Used To Evaluate The Ml...mentioning

confidence: 99%