Open AccessVITAMIN D DEFICIENCY PREDICTION
Author(s) -
B Deekshitha,
S Varsha,
Sakilam Varsha,
Y. V. Pridhvidhar Reddy
Publication year - 2021
Publication title -
paripex indian journal of research
Language(s) - English
DOI - 10.36106/paripex/5306806
Subject(s) - sunlight , waist , body mass index , medicine , vitamin d and neurology , environmental health , naive bayes classifier , machine learning , computer science , physics , astronomy , support vector machine
Vitamin D Deficiency (VDD) is one of the most significant global health problem and there is a strong demand for theprediction of its severity. The independent parameters like age, sex, weight, height, body mass index (BMI), waistcircumference,body fat,bone mass,exercise,sunlight exposure,and milk consumption were used for prediction of VDD.Factors such as lack of sunlight exposure,low physical activity,poor dietary habits,lack of sleep and stress increase therisk of the impacts due to Vitamin D Deficiency.There are certain bad habits that increase the risk of VDD .This projectaims at predicting the occurrence of VDD using Gaussian Naive Bayes classifier and Random Forest Prediction classifier.