Disease Prediction using Machine Learning Techniques

Abstract

The rise of computer-based innovations in the medical sector has led in electronic data acquiring. Because of the abundance of information readily available medical practitioners have the challenge of acknowledging indications and identifying diseases at an early stage. A wrong diagnosis is a major cause of inadequate therapy and failure to diagnose a serious illness in medicine. This paper assesses person's symptoms for disease prediction. In this paper we took input of three disease symptoms and evaluated them to give the disease as an output. Naive Bayes Classifier, Logistic Regression, K-Nearest neighbour (KNN), Support Vector Machine (SVM) and Random Forest Algorithm have been implemented in this paper. Our paper focuses on prediction of best accuracy model and also on the technique of splitting the dataset which will give us a better accuracy.