Using Fuzzy Unordered Rule Induction Algorithm for Cancer Data Classification

This paper studies the use of fuzzy logic in analysis and classification of bioinformatics data. The specific character of the bioinformatics data, the large number of attributes and the corresponding small number of records, asks for methods that can process such data and induce comprehensible and easily interpretable IF-THEN classification rules. Applied experiments were performed using Breast cancer, Prostate cancer, Gastric cancer, Gastric intestinal disease and Healthy donor data sets using Fuzzy Unordered Rule Induction Algorithm (FURIA). The study also describes the working processes of FURIA algorithm. To test the classification results of the aforementioned data sets additional experiments were carried out using bioinformatics data sets frequently used in literature. The paper also gives conclusions about the parameters that influence classification results (by either increasing or decreasing the accuracy) or are neutral to classification results