Malaria Diagnosis System by Using ID3 Classification Algorithm

Abstract

Decision Tree algorithms are the most popular algorithms for classification in data mining field. The main goal of classification is prediction of the categorical labels (classes). In this system, ID3 algorithm is used to predict infection of malaria disease on patients by selecting training data (patients’ medical records), constructing decision model and adjust the model based on testing data (part of patients’ medical records). The constructed model is represented in the form of decision tree and classification rules. The choice of suitable model to predict malaria infection on patient can decide against the correctness of model (classifier accuracy). To get the best classifier accuracy, this system permits selecting no of records to train the system and remove unnecessary braches of tree.