Prediction of COVID-19 Cases in Malaysia by Using Machine Learning: A Preliminary Testing

Abrar Noor Akramin Kamarudin,Zurinahni Zainol,Nur Faeza Abu Kassim,Razinah Sharif

2021 International Conference of Women in Data Science at Taif University (WiDSTaif )（2021）

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摘要

Estimating the spread of disease like COVID-19 is a crucial task that can reduce its impact and help the authorities to respond. Currently, the number of active cases in Malaysia is less than 50% of the accumulated points. This paper will present the most accurate machine learning model to predict the number of new possibilities for 01/04-15/04/2020 (15 days). Notably, four machine learning models...

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关键词

COVID-19,Measurement,Neural networks,Machine learning,Predictive models,Multilayer perceptrons,Market research

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