Thyroid Prediction Using Machine Learning Algorithms

The paper has been written with the aim of making a machine learning model that will predict thyroid disease with better accuracy. Among different machine learning algorithms, we are using supervised machine learning algorithms like Random Forest, Support Vector Machine (SVM), and Logistic Regression to predict thyroid disease and to evaluate their performance in terms of accuracy. For prediction of the thyroid disease, we are using the dataset from the UCI repository. Data from the UCI repository has been combined and cleaned to detect whether the person is suffering from thyroid or not.