A Comparative Study on MMDBM Classifier Incorporating Various Sorting Procedure

Classification is one of the most important methods in data mining. These methods are used to extract meaningful information from large database which can be effectively used for predicting unknown class. The classifier based on decision tree is called Mixed Mode Data Base Miner (MMDBM) which is tested with different sorting techniques (merge sort, quick sort, radix sort) to compare the processing time to SLIQ classifier. In this paper, we carried out a comparative study on MMDBM classifier incorporating various sorting procedure by using Blood Pressure (BP) database, and finally the proposed method MMDBM classifier is one of the best classifiers among SLIQ supervised learning method. This proposed method achieved less processing time and higher rate of accuracy.