e-ISSN : 0975-3397
Print ISSN : 2229-5631
Home | About Us | Contact Us

ARTICLES IN PRESS

Articles in Press

ISSUES

Current Issue
Archives

CALL FOR PAPERS

CFP 2021

TOPICS

IJCSE Topics

EDITORIAL BOARD

Editors

Indexed in

oa
 

ABSTRACT

Title : The Importance of Feature Selection in Classification
Authors : Mrs.K. Moni Sushma Deep, Mr. P.Srinivasu
Keywords : Feature Selection, Naïve Bayes, K-Nearest Neighbor and Classification Accuracy
Issue Date : January 2014.
Abstract :
Feature Selection is an important technique for classification for reducing the dimensionality of feature space and it removes redundant, irrelevant, or noisy data. In this paper the feature are selected based on the ranking methods. (1) Information Gain (IG) attribute evaluation, (2) Gain Ratio (GR) attribute evaluation, (3) Symmetrical Uncertainty (SU) attribute evaluation. This paper evaluates the features which are derived from the 3 methods using supervised learning algorithms K-Nearest Neighbor and Naïve Bayes. The measures used for the classifier are True Positive, False Positive, Accuracy and they compared between the algorithm for experimental results. we have taken 2 data sets Pima and Wine from UCI Repository database.
Page(s) : 63-68
ISSN : 0975–3397
Source : Vol. 6, Issue.01

All Rights Reserved © 2009-2024 Engg Journals Publications
Page copy protected against web site content infringement by CopyscapeCreative Commons License