Hybridized dimensionality reduction method for machine learning based web pages classification
Author
Source
Iraqi Journal of Computer, Communications and Control Engineering
Issue
Vol. 22, Issue 3 (30 Sep. 2022), pp.97-110, 14 p.
Publisher
Publication Date
2022-09-30
Country of Publication
Iraq
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Abstract EN
Feature space high dimensionality is a well-known problem in text classification and web mining domains, it is caused mainly by the large number of vocabularies contained within web documents.
Several methods were applied to select the most useful and important features over the years; however, the performance of such methods is still improvable from different aspects such as the computational cost and accuracy.
This research presents an enhanced cosine similarity-based hybridization of two efficient feature selection methods for higher classification performance.
The reduced feature sets are generated using the Random Projection (RP) and the Principal Component Analysis (PCA) methods, individually, then hybridized based on the cosine similarity values between features’ vectors.
The performance of the proposed method in terms of accuracy and F-measure was tested on a dataset of web pages based on several term weighting schemes.
As compared to relevant methods, results of the proposed method show significantly higher accuracy and f-measure performance based on less feature set size
American Psychological Association (APA)
Sabah, Thabit Sulayman. 2022. Hybridized dimensionality reduction method for machine learning based web pages classification. Iraqi Journal of Computer, Communications and Control Engineering،Vol. 22, no. 3, pp.97-110.
https://search.emarefa.net/detail/BIM-1492789
Modern Language Association (MLA)
Sabah, Thabit Sulayman. Hybridized dimensionality reduction method for machine learning based web pages classification. Iraqi Journal of Computer, Communications and Control Engineering Vol. 22, no. 3 (Sep. 2022), pp.97-110.
https://search.emarefa.net/detail/BIM-1492789
American Medical Association (AMA)
Sabah, Thabit Sulayman. Hybridized dimensionality reduction method for machine learning based web pages classification. Iraqi Journal of Computer, Communications and Control Engineering. 2022. Vol. 22, no. 3, pp.97-110.
https://search.emarefa.net/detail/BIM-1492789
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 108-109
Record ID
BIM-1492789