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Effect of Feature Selection Using Best First Search on the Performance of Classification
Authors(2) :-Bhavesh Patankar, Dr. Vijay Chavda
Performance in terms of high accuracy is very much required to any data mining system. A very much influencing factor on the success or failure of the data mining process is the quality of data used in the process. Feature selection is one of the preprocessing techniques in data mining which can prepare a quality data set before feeding it into the data mining process. This paper focuses on the Best First Search technique of feature selection. Feature selection is done using Best First Search. After selecting the features in given data set, it is taken as an input to the data mining process. It is observed that when classification is performed with feature selection, performance of classifier Performance of the classification. The success of a data mining problem heavily depends upon the quality of the data which is the most influencing factor. Moreover, feature selection represents one of the tools which can refine a dataset before presenting it to a learning scheme. In this paper, analyses of a wrapper approach for feature selection, with the purpose of boosting the classification accuracy is done. Experimental evaluations have been performed of feature selection on several data sets. The results showed that feature selection improves the overall performance in classification. Accuracy and speeds up the training process.
Bhavesh Patankar, Dr. Vijay Chavda
Data Mining; Classification; Preprocessing; Feature Selection;
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Published in : Volume 2 | Issue 5 | September-October 2016
Date of Publication : 2016-10-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 01-03
Manuscript Number : IJSRST16253
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
Bhavesh Patankar, Dr. Vijay Chavda, "Effect of Feature Selection Using Best First Search on the Performance of Classification ", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 2, Issue 5, pp.01-03, September-October-2016
URL : http://ijsrst.com/IJSRST16253