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http://dx.doi.org/10.14372/IEMEK.2020.15.6.307

A Study on Development Environments for Machine Learning  

Kim, Dong Gil (Gangwon EMbedded Software Cooperative Research Center)
Park, Yong-Soon (Gangwon EMbedded Software Cooperative Research Center)
Park, Lae-Jeong (Gangneung-Wonju National University)
Chung, Tae-Yun (Gangneung-Wonju National University)
Publication Information
IEMEK Journal of Embedded Systems and Applications / v.15, no.6, 2020 , pp. 307-316 More about this Journal
Abstract
Machine learning model data is highly affected by performance. preprocessing is needed to enable analysis of various types of data, such as letters, numbers, and special characters. This paper proposes a development environment that aims to process categorical and continuous data according to the type of missing values in stage 1, implementing the function of selecting the best performing algorithm in stage 2 and automating the process of checking model performance in stage 3. Using this model, machine learning models can be created without prior knowledge of data preprocessing.
Keywords
Machine Learning; Supervised Learning; Feature Engineering; Data Preprocessing; Algorithm;
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Times Cited By KSCI : 16  (Citation Analysis)
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