Fuzzy Classification to Identify the Risk in Diabetic Pregnancy

Abstract

There are different algorithms used in classification and these algorithm mainly used for classifying the algorithm accurately and the concept of fast classification is lagging behind in the previous algorithms. In this paper we introduce the new concept of Fuzzy Classification Algorithm (FCA) with the hybrid of ID3 and SVM. To make this algorithm with fast and accurate classification we use entropy to reduce the attributes which does not give more information and with use of lower and upper approximation for accuracy classification. The result of experiments shows that the improved fast classification algorithm considerably reduces the computational complexity and improves the speed of classification particularly in the circumstances of the large database.