Abstract : This paper proposes several feature selection and classification procedures for thyroid ailment diagnosis, which is one of the most critical classification issues. Two Thyroid disease refers to a set of disorders affecting the thyroid gland, which produces thyroid hormones. Hormones are in charge of controlling the pace of metabolism in the body. Hyperthyroidism and hypothyroidism are two types of thyroid diseases. They are classified. Thyroid disease is a challenging issue to resolve. The process of extracting or choosing a group of features is an important challenge in the field of pattern recognition. This is a step in the pre-processing process. As an example, consider the word sequence. The words "sequence backward selection" and "ahead selection" are used interchangeably. Two well-known heuristic approaches are utilized for feature extraction. selection. Genetics is a science.
In the health system, where there is a huge amount of data and information to manage, machine learning algorithms are essential for dealing with data. Our study on thyroid disease employed machine learning techniques. With the aim of classifying thyroid disease into three groups—hyperthyroidism, hypothyroidism, and normal—we conducted this study using data from Iraqi individuals, some of whom have hyperthyroidism and others who have hypothyroidism.

Keyword : AdaBoost, Decision Tree, Support Vector Machines and XgBoost.