International Journal of Emerging Trends in Science & Technology

E. Balraj ¹, P. Deepa ¹

Affiliations
1 Computer Science and Engineering, M. Kumarasamy College of Engineering, Karur, IN

Abstract

Ant Colony Optimization (ACO) algorithms have been successfully applied to discover a list of classification rules. In general, these algorithms follow a sequential covering strategy, where a single rule is discovered at each iteration of the algorithm in order to build a list of rules. The problem in this case is not coping with the problem of rule interaction, i.e., the result of a rule affects the rules that can be discovered subsequently since the search space is modified due to the removal of examples covered by previous rules. Here, a new sequential covering strategy cAnt-MinerPB for ACO classification algorithm is proposed to mitigate the problem of rule interaction, where the order of the rules is implicitly encoded as pheromone values and the search is guided by the quality of a candidate list of rules. cAnt-MinerPB algorithm, which is the extended version of the Ant-Miner algorithm that handles continuous attributes on-the-fly during the rule construction process. The experiments are conducted using 18 publicly available data sets and results shows that the predictive accuracy obtained by a new ACO classification algorithm implementing the cAnt- MinerPB, statistically significantly higher than the predictive accuracy of state-of-the-art rule induction classification algorithms.

Keywords

Datamining, Ant Colony Optimization, Classification, Rule Induction, Sequential Covering.

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E. Balraj ¹, T. Abirami ²

Affiliations
1 Assistant Professor, Department of Information Technology, M.Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
2 Associate Professor, Department of Information Technology, Kongu Engineering College, Perundurai, Tamil Nadu, IN

Abstract

In recent days, Biometrics becomes essential part of our life. Because it provides more security than other properties. People can apply biometric authentication in any field such as online exam, door access control, banking, identifying people, intelligent agent. The intelligent house becomes standard for the past few years. It will give a security and cozy to the house owner. However, the protection is incredibly necessary, it should be determining the house owner accurately and forestall the system to create an error for identification. Our proposed frameworks use finger print, facial recognition to make a system just like the security to create a identity and observation the protection of building

Keywords

Finger Print, Face Recognition, Smart Home Door, Multi Biometric, Intelligent House

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