An efficient SKNN based approach for heart disease classification

An efficient span-k-nearest neighbour (SKNN) algorithm has been proposed. It is used for the categorization of heart disease. The objective is to differentiate the data and find the accuracy of detection. The pre-processing is done based on the three attributes combination that is two, three and four with the help of KNN method. Then it is categorized based on five different spans that are 100, 125, 150, 200 and 250. The proposed work is compared with different factors of SKNN so that the proper capability can be explored. The obtained results show that the proposed approach has the significant capability of better classification.