Classification Model Using Optimization Technique: A Review

Abstract
Authors
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Conclusion
References

Data Mining is widely used in Sciences and technology fields. Classification is essential and important technique in data mining. Classification technique contains different types of classifiers. Decision Tree is most useful ruled based classifier, the rules are in the form of IF-THEN rules and generate it according to applicable conditions in tree structure, and checks all condition for classifying the data. The research of this project is that, Decision Tree is designing by greedy approach which is used to generate decision for each and every attributes, but the demerits of classification technique is generating number of rules during classification, it tends to less accuracy and efficiency. Resolved this disadvantage with the help of Artificial Bee Colony Optimization Algorithm. It is used to optimize rules and update the conditions during classification and optimized result. Therefore, classification using optimization algorithm is increasing accuracy and efficiency of classification model.

Published In : IJCSN Journal Volume 6, Issue 1

Date of Publication : February 2017

Pages : 42-48

Figures :02

Tables : --

Deoshree Diwathe : M. Tech Computer Science & Engineering, G. H. Raisoni College of Engineering, Nagpur, India.

Snehlata S.Dongare : Computer Science and Engineering, G. H. Raisoni College of Engineering, Nagpur, India.

Data Mining, Classification technique, Decision Tree Classifier, Artificial Bee Colony Optimization Algorithm(ABC Optimization Algorithm)

In this paper, Artificial Bee Colony Optimization Algorithm is applicable for classification which is very robust and efficient algorithm. An ABC algorithm is useful for train the dataset and updates the weights, because of this purpose it is very flexible in nature and minimizes the number of rules created by decision tree algorithm. Finally, it improves accuracy and efficiency.

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