International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 50 - Number 14 |
Year of Publication: 2012 |
Authors: J. S. Raikwal, Kanak Saxena |
10.5120/7842-1055 |
J. S. Raikwal, Kanak Saxena . Performance Evaluation of SVM and K-Nearest Neighbor Algorithm over Medical Data set. International Journal of Computer Applications. 50, 14 ( July 2012), 35-39. DOI=10.5120/7842-1055
In this age of computer science each and every thing becomes intelligent and perform task as human. For that purpose there are various tools, techniques and methods are proposed. Support vector machine is a model for statistics and computer science, to perform supervised learning, methods that are used to make analysis of data and recognize patterns. SVM is mostly used for classification and regression analysis. And in the same way k-nearest neighbor algorithm is a classification algorithm used to classify data using training examples. In this paper we use SVM and KNN algorithm to classify data and get prediction (find hidden patterns) for target. Here we use medical patients nominal data to classify and discover the data pattern to predict future disease, Uses data mining which is use to classify text analysis in future.