Detection of Thyroid using Different Machine Learning Approach

Abstract

The purpose of this paper is to identify the diagnosis of thyroid disease and to classify the two possible types of thyroid disease (hypothyroidism and hyperthyroidism). Numerous machine-learning algorithms are currently being used to identify thyroid disease. Nonetheless, our goal is to implement the machine learning algorithm, which will allow for faster and more accurate diagnosis of thyroid disease and type. The project is being implemented in Python, and the platform from which the dataset was derived is Kaggle. The Kaggle dataset was trained using a variety of machine-learning techniques. In addition, we have attempted to reduce the number of disease detection parameters.