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Title: :  Applying Machine Learning Algorithms For The Classification Of Sleep Disorders
PaperId: :  26123
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 11 Issue 2 2025
DUI:    16.0415/IJARIIE-26123
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
SIVASANKAR CHITTOORSiddharth Institute of Engineering and Technology
BOLIGORLA VIDYASiddharth Institute of Engineering and Technology
N.U. DHARSHANSiddharth Institute of Engineering and Technology
A. GEETHASiddharth Institute of Engineering and Technology
A.ROHITHSiddharth Institute of Engineering and Technology
SHIVAM KUMARSiddharth Institute of Engineering and Technology

Abstract

Information Technology
Sleep Disorders, Machine Learning, Stacking Classifier, Voting Classifier, Sleep Apnea, Insomnia
Sleep disorder classification is crucial in improving human quality of life. Sleep disorders and apnoea can have a significant influence on human health. Sleep-stage classification by experts in the field is an arduous task and is prone to human error. The development of accurate machine learning algorithms (MLAs) for sleep disorder classification requires analysing, monitoring and diagnosing sleep disorders. This paper compares deep learning algorithms and conventional MLAs to classify sleep disorders. This study proposes an optimised method for the Classification of Sleep Disorders and uses the Sleep Health and Lifestyle Dataset publicly available online to evaluate the proposed model. The optimisations were conducted using a genetic algorithm to tune the parameters of different machine learning algorithms. An evaluation and comparison of the proposed algorithm against state-of-the-art machine learning algorithms to classify sleep disorders. The dataset includes 400 rows and 13 columns with various features representing sleep and daily activities. The k-nearest neighbours, support vector machine, decision tree, random forest and artificial neural network (ANN) deep learning algorithms were assessed. The experimental results reveal significant performance differences between the evaluated algorithms. The proposed algorithms obtained a classification accuracy of 83.19%, 92.04%, 88.50%, 91.15% and 92.92%, respectively. The ANN achieved the highest classification accuracy of 92.92%, and its precision, recall and F1-score values on the testing data were 92.01%, 93.80% and 91.93%, respectively. The ANN algorithm that achieved high accuracy than other tested algorithms.

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IJARIIE SIVASANKAR CHITTOOR, BOLIGORLA VIDYA, N.U. DHARSHAN, A. GEETHA, A.ROHITH, and SHIVAM KUMAR. "Applying Machine Learning Algorithms For The Classification Of Sleep Disorders" International Journal Of Advance Research And Innovative Ideas In Education Volume 11 Issue 2 2025 Page 1366-1378
MLA SIVASANKAR CHITTOOR, BOLIGORLA VIDYA, N.U. DHARSHAN, A. GEETHA, A.ROHITH, and SHIVAM KUMAR. "Applying Machine Learning Algorithms For The Classification Of Sleep Disorders." International Journal Of Advance Research And Innovative Ideas In Education 11.2(2025) : 1366-1378.
APA SIVASANKAR CHITTOOR, BOLIGORLA VIDYA, N.U. DHARSHAN, A. GEETHA, A.ROHITH, & SHIVAM KUMAR. (2025). Applying Machine Learning Algorithms For The Classification Of Sleep Disorders. International Journal Of Advance Research And Innovative Ideas In Education, 11(2), 1366-1378.
Chicago SIVASANKAR CHITTOOR, BOLIGORLA VIDYA, N.U. DHARSHAN, A. GEETHA, A.ROHITH, and SHIVAM KUMAR. "Applying Machine Learning Algorithms For The Classification Of Sleep Disorders." International Journal Of Advance Research And Innovative Ideas In Education 11, no. 2 (2025) : 1366-1378.
Oxford SIVASANKAR CHITTOOR, BOLIGORLA VIDYA, N.U. DHARSHAN, A. GEETHA, A.ROHITH, and SHIVAM KUMAR. 'Applying Machine Learning Algorithms For The Classification Of Sleep Disorders', International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 2, 2025, p. 1366-1378. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Applying_Machine_Learning_Algorithms_For_The_Classification_Of_Sleep_Disorders_ijariie26123.pdf (Accessed : ).
Harvard SIVASANKAR CHITTOOR, BOLIGORLA VIDYA, N.U. DHARSHAN, A. GEETHA, A.ROHITH, and SHIVAM KUMAR. (2025) 'Applying Machine Learning Algorithms For The Classification Of Sleep Disorders', International Journal Of Advance Research And Innovative Ideas In Education, 11(2), pp. 1366-1378IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Applying_Machine_Learning_Algorithms_For_The_Classification_Of_Sleep_Disorders_ijariie26123.pdf (Accessed : )
IEEE SIVASANKAR CHITTOOR, BOLIGORLA VIDYA, N.U. DHARSHAN, A. GEETHA, A.ROHITH, and SHIVAM KUMAR, "Applying Machine Learning Algorithms For The Classification Of Sleep Disorders," International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 2, pp. 1366-1378, Mar-App 2025. [Online]. Available: https://ijariie.com/AdminUploadPdf/Applying_Machine_Learning_Algorithms_For_The_Classification_Of_Sleep_Disorders_ijariie26123.pdf [Accessed : ].
Turabian SIVASANKAR CHITTOOR, BOLIGORLA VIDYA, N.U. DHARSHAN, A. GEETHA, A.ROHITH, and SHIVAM KUMAR. "Applying Machine Learning Algorithms For The Classification Of Sleep Disorders." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 11 number 2 ().
Vancouver SIVASANKAR CHITTOOR, BOLIGORLA VIDYA, N.U. DHARSHAN, A. GEETHA, A.ROHITH, and SHIVAM KUMAR. Applying Machine Learning Algorithms For The Classification Of Sleep Disorders. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2025 [Cited : ]; 11(2) : 1366-1378. Available from: https://ijariie.com/AdminUploadPdf/Applying_Machine_Learning_Algorithms_For_The_Classification_Of_Sleep_Disorders_ijariie26123.pdf
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