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Senthamilarasu, S.
- A Genetic Algorithm Based Intuitionistic Fuzzification Technique for Attribute Selection
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Authors
Affiliations
1 Department of Computer Science, Karpagam University, Coimbatore-21, TN, IN
1 Department of Computer Science, Karpagam University, Coimbatore-21, TN, IN
Source
Indian Journal of Science and Technology, Vol 6, No 4 (2013), Pagination: 4336-4346Abstract
This paper initiates perceptions and algorithms of feature selection, survey of existing feature selection algorithms and assesses diverse algorithms with a classifying frame based on search approaches, valuation criteria, and provides strategy in selecting feature selection algorithms. A unifying platform is projected to continue our efforts headed for building an incorporated system for intelligent feature selection. Feature selection intends to reduce the dimensionality of patterns for classification by choosing the most informative instead of irrelevant and/or redundant features. In this proposed work Intuitionistic fuzzy based feature clustering is proposed for grouping features based on the degree of membership and degree of indeterminacy among the attributes and clusters. In this proposed work a novel approach which uses an Intuitionistic fuzzy version of k-means has been introduced for grouping interdependent features. Genetic algorithm reinstating which is the variation of traditional genetic algorithm is then applied to appraise whether the measured feature is independent of class labels; hence, it leads to eliminate unrelated clusters to classification process and progress the selection of features. The proposed method achieves improvement on classification accuracy and perhaps to select less number of features which show the way to simplification of learning task to a big extent. The Experiment results have been demonstrated by the good performance and also find good enough subset features of this method on using UCI benchmark datasets that are for data mining methods such as Breast Cancer, Sensor and Iris Records.Keywords
Feature Selection, Cluster, Genetic, K-means, Fuzzy, IntuitionisticFull Text
References
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- Speech Sensor Based Riding Protection Using PIC Micro Controller
Abstract Views :132 |
PDF Views:3
Authors
Affiliations
1 P. A. College of Engg and Tech, IN
2 IV ECE, P. A. College of Engg and Tech, IN
1 P. A. College of Engg and Tech, IN
2 IV ECE, P. A. College of Engg and Tech, IN
Source
Biometrics and Bioinformatics, Vol 7, No 2 (2015), Pagination: 52-54Abstract
Accidents are the unexpected events which causes a loss of life, economy and welfare of both the victims. As per the statistics released by WHO (World Health Organisation), it is found that more than 10%of global accidents occur in India alone. Among that drunken drive and usage of mobile phones accounts more than 70% .Excess alcoholic content in our body during riding may causes the rider to impair ability, degrade performance and result in serious sickness. Real time sensing of alcohol content in human body is thus an important research nowadays. This paper majorly deals with usage of alcoholic sensor and a speech recognition based sensor. Victims who meet with accidents may suffer lots of head injuries which are due to the fact that not wearing helmet during riding. So our project focuses to make helmet as an unavoidable life saver. As our government also taking steps to make helmet as a compulsory one but it can’t be implemented successfully .our project helps for this task to be implemented successfully.
