NDLI: Improved Adaboost Algorithm for Classification Based on Noise Confidence Degree and Weighted Feature Selection

Content Provider	Directory of Open Access Journals (DOAJ)
Author	Youwei Wang Lizhou Feng
Abstract	Adaboost is a typical ensemble learning algorithm and has been studied and widely used in classification tasks. In order to improve the classification performance of existing Adaboost algorithms effectively, a noise confidence degree and weighted feature selection based Adaboost algorithm (called NW_Ada) is proposed. Firstly, in order to decrease the impact of sample set density on noise detection results, the conceptions of clustering degree and deviated degree are introduced, and a new method of evaluating the noise confidence is proposed. Then, based on the traditional feature selections of filters, a weighted feature selection method is proposed to select the features which can effectively distinguish the samples those are misclassified. Finally, based on the traditional error rate calculation method, the category recall based classifier error rate calculation method is proposed to solve the problem that the traditional methods ignore the distribution of misclassified samples when dealing with the unbalanced datasets. The experimental results show that the proposed method comprehensively considers the influences of sample density, sample weight and dataset size on classification results, and obtains significant improvement on classification performance compared to traditional Adaboost algorithms when different datasets especially the unbalanced datasets are used.
e-ISSN	21693536
DOI	10.1109/ACCESS.2020.3017164
Journal	IEEE Access
Volume Number	8
Language	English
Publisher	IEEE
Publisher Date	2020-01-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Electrical Engineering. Electronics. Nuclear Engineering Ensemble Learning Feature Selection Error Rate Classifier Weight Sample Density
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in