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Parham Moradi

Parham Moradi

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId: 654
Faculty: Faculty of Engineering
Address: Department of Computer Engineering, Faculty of Engineering, University of Kurdistan
Phone:

Research

Title
Feature selection based on hybridization of Information gain and graph clustering for text classification
Type
Presentation
Keywords
Feature selection, Information gain, text categorization, Feature clustering.
Year
2019
Researchers Parham Moradi ، Fatemeh Zamani ، Alireza Abdollahpouri ، Shadi Rahimi

Abstract

Text datasets usually have a lot of features. Therefore, theirs classification cost is too much and feature selection in this context is of vital importance. In this paper, a novel feature selection method based on information gain and FAST algorithm is proposed. In the proposed method, at first, the features with higher information gain are selected. Then, the FAST algorithm on the selected features is applied. Experiments are carried out to compare our algorithm with several feature selection techniques. The new approach is tested on three text datasets. The results confirm that the proposed method produces smaller feature subset in shorter time. The evaluation of a K-nearest neighborhood classifier on validation data show that, the novel algorithm gives higher classification accuracy.