SAA Balamurugan, R Rajaram - International Journal of Automation and …, 2009 - Springer
This paper proposes one method of feature selection by using Bayes' theorem. The purpose of the proposed method is to reduce the computational complexity and increase the …
Prediction plays a vital role in decision making. Correct prediction leads to right decision making to save the life, energy, efforts, money and time. The right decision prevents physical …
K Mani, P Kalpana - International Journal of Information Engineering …, 2016 - mecs-press.org
Feature selection is an indispensable pre-processing technique for selecting more relevant features and eradicating the redundant attributes. Finding the more relevant features for the …
S Koul, R Chhikara - Int. J. Eng. Tech. Res, 2015 - academia.edu
Feature selection techniques have turned into a clear need in numerous applications. Feature Selection removes redundant or irrelevant features and can improve the accuracy of …
M Last, A Kandel, O Maimon - Pattern Recognition Letters, 2001 - Elsevier
Feature selection is used to improve the efficiency of learning algorithms by finding an optimal subset of features. However, most feature selection techniques can handle only …
J Palanichamy, K Ramasamy - 2013 International Conference …, 2013 - ieeexplore.ieee.org
The purpose of the feature selection is to eliminate insignificant features from entire dataset and simultaneously to keep the class discriminatory information for classification problems …
K Lee - Proceedings of MASPLAS, 2002 - academia.edu
This paper proposes a feature selection method that combines various feature selection techniques. Feature selection has been realized as one of the most important processes in …
P Kalpana, K Mani - International journal of engineering, 2017 - ije.ir
Feature selection is a pre-processing technique used for eliminating the irrelevant and redundant features which results in enhancing the performance of the classifiers. When a …
S Singh, S Selvakumar - International Conference on …, 2015 - ieeexplore.ieee.org
The presence of a large number of irrelevant features degrades the classifier accuracy, reduces the understanding of data, and increases the overall time needed for training and …