Diagnosis of Malarias by Using Reduct Generation Algorithm

Abstract

Data mining aims to discover novel, interesting and useful knowledge and patterns from databases. Data Classification is the process of building a model from available data called the training data set and classifying objects according to their attributes. The rough set theory is used to identify the most important attributes and to induce decision rules from symptoms diseases. This system is intended to develop the diagnosis of malarias patient’s symptoms by using reduct generation algorithm under the set theory. Multi features reducts are produced by using reduct generation algorithm from rough set theory. In the diagnosis of malarias patients, the reducts are useful in classifying data. The malarias diagnosis system includes 23 attributes (symptoms) and 4 classes (diseases). This system provides the malarias disease results to patients according to the symptoms that they are suffered.