Feature wise normalization: An effective way of normalizing data
作者：
Highlights：
• A novel approach feature-wise normalization (FWN) has been presented to normalize the data.
• FWN normalizes each feature independently from the pools of normalization methods.
• The collective response of multiple methods mitigates the problems of outliers and dominant features more effectively.
• Antlion optimization is used to search for normalization methods along with the parameters of classifiers.
• FWN outperformed conventional data-wise normalization on four popular machine learning algorithms.
摘要
A novel approach feature-wise normalization (FWN) has been presented to normalize the data.•FWN normalizes each feature independently from the pools of normalization methods.•The collective response of multiple methods mitigates the problems of outliers and dominant features more effectively.•Antlion optimization is used to search for normalization methods along with the parameters of classifiers.•FWN outperformed conventional data-wise normalization on four popular machine learning algorithms.
论文关键词：Data normalization,k-nearest neighbor classification,Machine learning,Metaheuristic optimization,Naive bayes classification,Neural networks,Support vector machines
论文评审过程：Received 10 August 2020, Revised 18 May 2021, Accepted 6 September 2021, Available online 20 September 2021, Version of Record 26 September 2021.
论文官网地址：https://doi.org/10.1016/j.patcog.2021.108307
