NDLI: An Enhanced K-Nearest Neighbor Algorithm Using Information Gain and Clustering

Content Provider	IEEE Xplore Digital Library
Author	Taneja, S. Gupta, C. Goyal, K. Gureja, D.
Copyright Year	2014
Description	Author affiliation: CSE Dept., Guru Gobind Singh Indraprastha Univ., New Delhi, India (Taneja, S.; Gupta, C.; Goyal, K.; Gureja, D.)
Abstract	KNN (k-nearest neighbor) is an extensively used classification algorithm owing to its simplicity, ease of implementation and effectiveness. It is one of the top ten data mining algorithms, has been widely applied in various fields. KNN has few shortcomings affecting its accuracy of classification. It has large memory requirements as well as high time complexity. Several techniques have been proposed to improve these shortcomings in literature. In this paper, we have first reviewed some improvements made in KNN algorithm. Then, we have proposed our novel improved algorithm. It is a combination of dynamic selected, attribute weighted and distance weighted techniques. We have experimentally tested our proposed algorithm in Net Beans IDE, using a standard UCI dataset-Iris. The accuracy of our algorithm is improved with a blend of classification and clustering techniques. Experimental results have proved that our proposed algorithm performs better than conventional KNN algorithm.
Sponsorship	IEEE Harbin Sect.
Starting Page	325
Ending Page	329
File Size	123006
Page Count	5
File Format	PDF
ISBN	9781479949106
DOI	10.1109/ACCT.2014.22
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-02-08
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Classification algorithms Clustering algorithms Training Heuristic algorithms Algorithm design and analysis Euclidean distance Data mining Information Gain KNN Dynamic KNN (DKNN) Distance-Weighted KNN (DWKNN) Weight Adjusted KNN
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 Libarray 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

MFZ-KNN — A modified fuzzy based K nearest neighbor algorithm

Dynamic K-Nearest-Neighbor with Distance and attribute weighted for classification

Classification of pancreas tumor dataset using adaptive weighted k nearest neighbor algorithm

A weighting approach for KNN classifier

Nearest Neighbor Classification by Partially Fuzzy Clustering

The k-Nearest Neighbor Algorithm Using MapReduce Paradigm

K-nearest neighbor classification on spatial data streams using p-trees (2002).

Weigted-KNN and its application on UCI

A performance comparison between classification techniques with CRM application

An Enhanced K-Nearest Neighbor Algorithm Using Information Gain and Clustering

Similar Documents

MFZ-KNN — A modified fuzzy based K nearest neighbor algorithm

Dynamic K-Nearest-Neighbor with Distance and attribute weighted for classification

Classification of pancreas tumor dataset using adaptive weighted k nearest neighbor algorithm

A weighting approach for KNN classifier

Nearest Neighbor Classification by Partially Fuzzy Clustering

The k-Nearest Neighbor Algorithm Using MapReduce Paradigm

K-nearest neighbor classification on spatial data streams using p-trees (2002).

Weigted-KNN and its application on UCI

A performance comparison between classification techniques with CRM application

An Enhanced K-Nearest Neighbor Algorithm Using Information Gain and Clustering