Sleep Quality Analysis Based on Logistical, SVC and Xgboost
DOI:
https://doi.org/10.54097/7bfdy131Keywords:
Sleep health; logistical model; SVC; Xgboost.Abstract
As a matter of fact, a healthy lifestyle requires sleep quality to be one of the main ingredients. It's a common practice to spend roughly a third of the lives sleeping, or at the very least, one should. Regrettably, that goal is not met by many of human beings in recent years. With this in mind, this study will investigate to build three models LogisticRegression Model, XGBClassifier Model, SVC Model using python technique. From the acquired data the model is used to find out some lifestyle effects on sleep. XGBClassifier Model is selected as the best model for the study. The model concluded that Occupation has the greatest effect on insomnia. Sleep apnea is most affected by BMI Category. BMI Category, Stress Level, Blood Pressure, Sleep Duration have more influence on sleep. These results show that the quality of sleep can be improved in terms of BMI Category and Blood Pressure.
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