International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 3 May-June 2024 Submit your research before last 3 days of June to publish your research paper in the issue of May-June.

Sleep Quality Prediction From Wearable Device Data: A Comprehensive Analysis and Model Comparison

Author(s) Hema Nagendra Sai Chanda
Country India
Abstract This study explores machine learning techniques for predicting sleep quality from wearable device data. It compares classification and regression approaches, including Random Forest, Gradient Boosting, and deep learning models like RNNs and CNNs. Results highlight the effectiveness of these models and offer insights into optimal algorithms and feature selection for accurate sleep quality prediction.
Keywords Classification, Convolutional Neural Networks, Gradient Boosting, Machine Learning, Random Forest, Regression, Recurrent Neural Networks, Sleep Quality Prediction, Wearable Devices
Field Computer
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-05-16
Cite This Sleep Quality Prediction From Wearable Device Data: A Comprehensive Analysis and Model Comparison - Hema Nagendra Sai Chanda - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.20501
DOI https://doi.org/10.36948/ijfmr.2024.v06i03.20501
Short DOI https://doi.org/gtvtx9

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