Abnormal eating behavior which has a negative impact on a human body is called an eating disorder. Eating disorders generally occur in teenage years and cause disturbances in diet and health. There are various types of eating disorders where the two most prominent types are Anorexia Nervosa (AN) and Bulimia Nervosa (BN). Anorexia refers to eating in very small quantities which is not sufficient to a human body and Bulimia refers to heavy or excess eating which is harmful as well. In this paper, the focus was on Anorexia Nervosa. People in anorexia tend to over consciously control their weight and shape. In order to prevent weight gain, people with anorexia strictly limit the amount of food they consume, they even vomit purposely after eating to reduce the calorie intake or even take misleading medicines to control their weight. The disease can take over one’s life and can be very tough to overcome. But proper treatment can help an individual to get to know themselves and move towards a healthier lifestyle. For people to be able to recognize if they have this disease or not, have developed a machine learning model using logistic regression to predict the possibility of Anorexia. The used dataset is a valuation in adults with a history of anorexia nervosa from Department of Neuroscience, University of Pennsylvania published by Duke Digital Repository. The dataset consists of records of people who are suffering from this disease. It consists of various factors like current BMI, age etc.

Eating Disorder Logistic Regression