Music Prediction for Music Therapy using Random Forest

  • Devendran K, Keerthika P, Manjula Devi R, Ponnarasee B K, Raj Bharath S, Sabeena Yashmin J B

Abstract

People experience stress due to various factors like work pressure, emotional problems, disaster, violence, etc in their day to day life. This stress leads to many physical and mental health risk such as Asthma, Headaches, Anxiety, heart disease, Depression, Asthma, Alzheimer’s disease, etc. Music therapy has the ability to balance both the physical and mental fitness of humans. Music therapy is a healing process that uses music to an inscription the emotional, physical, cognitive needs of a self one or a group. Here we aimed to establish the music classification and prediction for music therapy using a machine learning algorithm- Random forest. This study involves factors such as people's age, education status, music interest, preferences of music in both individual and therapist aspects, and their respective relaxation scale before and after music therapy. Our study reveals the important features involved in music prediction for music therapy and the accuracy performance of about 89 is achieved by this classification.

Published
2020-05-17
How to Cite
Devendran K, Keerthika P, Manjula Devi R, Ponnarasee B K, Raj Bharath S, Sabeena Yashmin J B. (2020). Music Prediction for Music Therapy using Random Forest. International Journal of Control and Automation, 13(4), 70 - 76. Retrieved from https://sersc.org/journals/index.php/IJCA/article/view/16051
Section
Articles