A Comparative Study of Gaussian Process Machine Learning and Time Series Analysis Techniques for Predicting Unemployment Rate

A Comparative Study of Gaussian Process Machine Learning and Time Series Analysis Techniques for Predicting Unemployment Rate

This study explores and compares the capability of Gaussian process machine learning (GPML) with time series analysis techniques, which are autoregressive integrated moving average (ARIMA), seasonal ARIMA (SARIMA) and cubic spline interpolation, in modeling unemployment rate in Malaysia over the per...

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Bibliographic Details
Published in:2024 16th International Conference on Computer and Automation Engineering, ICCAE 2024
Main Author: Aris M.N.M.; Nagaratnam S.; Zakaria N.N.; Mohd Azami M.F.A.; Samsudin M.A.I.; Othman E.S.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85198357359&doi=10.1109%2fICCAE59995.2024.10569432&partnerID=40&md5=e74843de516322667c0a3e37be73911f

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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85198357359&doi=10.1109%2fICCAE59995.2024.10569432&partnerID=40&md5=e74843de516322667c0a3e37be73911f

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