JIITA, vol.8 no.3, p.981-990, 2024, DOI: 10.22664/ISITA.2024.8.3.981
Sehyun Myeong, Yoosoo Oh
Daegu University
Abstract: We present a low code-based system that enables automatic application and prediction of learning algorithms regardless of data type. The proposed system automatically converts inputted data with discrete properties into continuous data and continuous properties into discrete data. The proposed system performs well even when discrete and continuous data are cross-applied to classification and regression
algorithms. Particularly, the data attribute is converted to fit the selected algorithm properly according to the type of algorithm. Accordingly, the proposed system can predict well even if the user applies inputted data to any algorithm without concern about inputted data properties.
Keywords: Discrete Data; Continuous Data; Regressor; Classifier; Machine Learning
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