1DEEPTHI SRAMBICAL POULOSE, 2DINESH KUMAR SAHU and 3ANIL RAJPUT

¹M. Tech Scholar, Department of CSE, Sri Satya Sai College of Engineering , Bhopal M.P. (India)
²Ph.D Scholar, Department of Computer Science, Barkatullah University, Bhopal M.P. (India)
³Professor, Department of Mathematics, CSA, Govt. P.G. College, Sehore M.P. (India)

Data Mining, WEKA, Decision Tree

July 2015

In this paper we used WEKA for finding decision tree approach in blood bank data. Data mining refers to extracting knowledge from large amount of data. Real life data mining approaches are interesting because they often present a different set of problems for data miners. Decision tree is a popular supervised learning classifier that does not require any knowledge or parameter setting. Given a training data, we can induce a decision tree. From a decision tree we can easily create rules about the data

2455-9997 (Online) - 2229-3531 (Print)

Vol.6 - No.1

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