Abstract
Music has a great impact on stress relieving for human. We have become very stressed by society and the times. Accumulated stress cannot be met daily, and this will have an adverse effect on our health and our mental health, such as obesity, heart attacks, insomnia, and so on. Therefore, this study has been offering an ensemble approach combining algorithms of machine learning such as K-NN, naïve Bayes, multilayer perceptron, and random forest for stress relief based on musical genres.
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Acknowledgements
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (No. 2017R1A2B4010826).
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Munkhbat, K., Ryu, K.H. (2020). Classifying Songs to Relieve Stress Using Machine Learning Algorithms. In: Pan, JS., Li, J., Tsai, PW., Jain, L. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 157. Springer, Singapore. https://doi.org/10.1007/978-981-13-9710-3_43
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