Thyroid Disease Classification using Machine Learning Algorithm

Several feature selection and classification strategies are proposed in this work for thyroid illness diagnosis, which is one of the most important classification challenges. Two Thyroid disease is a group of diseases that affect the thyroid gland, which produces thyroid hormones.  Hormones are responsible for regulating the rate of the body's metabolism.  Thyroid disorders include hyperthyroidism and hypothyroidism. These are categorised. Thyroid illness is a difficult problem to solve. A significant issue in the field of Pattern recognition is the process of extracting or selecting a set of features. This is part of the pre-processing stage. Sequential is used as an example. The terms "ahead selection" and "sequence backward selection" are used interchangeably.  For feature extraction, two well-known heuristic techniques are used.  selection. Genetics is another approach of feature selection that has been investigated. Algorithm, a common nonlinear optimization method issue. To separate the data, a support vector machine is utilised as a classifier. Thyroid disorders are a group of diseases that affect the thyroid gland.With thyroid disease, we applied machine learning techniques in our research. We worked on this study utilising data from Iraqi people, some of whom have an overactive thyroid gland and others who have hypothyroidism, with the purpose of categorising thyroid disease into three categories: hyperthyroidism, hypothyroidism, and normal.

Keywords: Decision Tree, AdaBoost, XGBoost, and Support Vector Machines.