Classification is a data mining technique used to predict group membership for data instances . There are several conventional methods for classification in data mining like Decision Tree Induction, Bayesian Classification, Rule-Based Classification, Classification by Backpropagation and classification by Lazy Learners. In this paper we propose a new modified tree for classification in Data Mining. The proposed modified Tree is inherited from the concept of the decision tree and knapsack problem. A very high dimensional data may be handled with the proposed tree and optimized classes may be generated.
Classification is a data mining technique used to predict group membership for data instances [1]. There are several conventional methods for classification in data mining like Decision Tree Induction, Bayesian Classification, Rule-Based Classification, Classification by Backpropagation and classification by Lazy Learners. In this paper we propose a new modified tree for classification in Data Mining. The proposed modified Tree is inherited from the concept of the decision tree and knapsack problem. A very high dimensional data may be handled with the proposed tree and optimized classes may be generated.