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Performance Analysis of Risk Factors of Obesity in Women using Artificial Neural Network

Obesity is becoming a global health issue for women which has emerged and reached epidemic proportions in developed countries. Along with obesity, anemia continues to be an epidemic in India and other nations, posing a double burden on society. This has major impact on children and teenagers as well as adults. Obese women are more prone to acquire conditions such as PCOS, Diabetes, Hypertension, and thyroid problems. Exploratory Data Analysis (EDA) is used to investigate the health hazards of obesity using data from health records. In this paper, the authors have considered the risk factors for obesity in women and has implemented prediction model. We have utilized Artificial Neural Network (ANN) and Generalized Logistic Regression Model (GLRM) to produce reliable predictions. These models are compared based on the performance criteria such as classification accuracy and stability. Generalized Logistic Regression (GLRM) uses the activation function of ANN to improve the accuracy and stability of the model.