Sleep Disorder Prediction using Machine Learning

Abstract

A medical disease known as a sleep disorder might interfere with your sleep patterns, quantity, or quality. Experiencing fatigue even after obtaining adequate sleep or waking up feeling unrefreshed are symptoms of sleep problems which come in a plethora of forms, with wildly disparate causes [8]. They are classified as two types of sleep disorders like Sleep Amnesia and Insomnia. In this work, authors investigate and analyze various machine learning algorithms for Sleep disorder prediction, such as Random Forest Classifier, SVC, Ridge Classifier, and Logistic Regression. Overall, the suggested ML learning-based prediction models performed similarly. Random forest algorithm turned out to be the best one when it comes to accuracy, precision and recall. Although Random Forest is the best one, other algorithms have been tried out and compared to get accurate prediction. Our work can predict the sleep disorder in people according to age, Occupation, BMI and many other factors.