Mamdani fuzzy inference system for breast cancer risk detection

Abstract

Diagnosing various diseases in medical field is very difficult even for medical expert. For solving this problem data mining was introduced. It discovers knowledge from the database. There are many subfields in data mining. One of the subfield is fuzzy logic. It is applied in many fields such as control theory, Artificial Intelligence (AI) and also in the field of medicine. This paper focuses on detecting the risk of breast cancer by using fuzzy logic. The dataset used in this work is retrieved from UCI machine learning repository. The aim of this proposed work is to detect the breast cancer by reducing the variables, so that it reduces the time taken for diagnosing the disease. The features were extracted by using one of the feature selection method called Linear Discriminant Analysis (LDA) and training is done by using one of the fuzzy inference method called Mamdani Fuzzy inference model. The results were evaluated by using the above model. It gave the result of 93%.