The automation of the development of classification models and improvement of model quality using feature engineering techniques
作者：
Highlights：
• We showed the versatility of our framework for rapid model deployment.
• We created classification models for the HRMS data and aimed to find the best one.
• We implemented a framework for automatically generating classification models.
• We showcased the applicable feature engineering techniques within this framework.
• We demonstrated the ways to improve model quality using this automation framework.
摘要
•We showed the versatility of our framework for rapid model deployment.•We created classification models for the HRMS data and aimed to find the best one.•We implemented a framework for automatically generating classification models.•We showcased the applicable feature engineering techniques within this framework.•We demonstrated the ways to improve model quality using this automation framework.
论文关键词：Machine learning pipeline,Feature engineering,Machine learning,Automation,Data imputation,Feature transformation,Data balancing
论文评审过程：Received 27 May 2022, Revised 12 September 2022, Accepted 23 September 2022, Available online 27 September 2022, Version of Record 1 October 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.118912
