Data Analysis on the Risks of Obesity and OverWeight in Women-A Study
Author(s):
Alamma BH, Dr. Manjula Sanjay Koti
Keywords:
Random Forest, Decision Tree, PCOS, diabetes, Hypertension.
Abstract
Health problems in women is increasing globally and obesity being the main one which is higher in females than males. Along with under nurtrition ,obesity as epidemic is continued as a problem in some countries, including India, as double burden This is not just affecting adults but also children and adolescents. Other risks are Polycystic ovary syndrome, blood Pressure, blood Sugar, Thyroid and others. It has emerged and reached epidemic proportions seen in industrialized countries. These factors affect more on women of reproductive age.Compared with normal-weight women, obese women are prone to develop diseases like PCOS, Diabetes, CVD, Hypertension etc.This paper analyzes health risks of obesity and also prediction of other health risks like PCOS, Diabetes, Hypertension and Thyroid using the data containing health records by exploratory data analysis and machine learning techniques respectively. We use Random Forest (RF) and Decision Tree (DT) classifiers for analysis of risk factors in women. The performance based on accuracy rate is measured by comparing with the two different classifiers.
Article Details
Unique Paper ID: 150688

Publication Volume & Issue: Volume 7, Issue 9

Page(s): 34 - 38
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Volume 7 Issue 9

Last Date 25 February 2020

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