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An Appraise of KNN to the Perfection
by
Pooja Rani,
Jyoti Vashishtha
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 170 - Number 2 |
| Year of Publication: 2017 |
| Authors: Pooja Rani, Jyoti Vashishtha |
10.5120/ijca2017914696
|
Pooja Rani, Jyoti Vashishtha . An Appraise of KNN to the Perfection. International Journal of Computer Applications. 170, 2 ( Jul 2017), 13-17. DOI=10.5120/ijca2017914696
@article{
10.5120/ijca2017914696,
author = {
Pooja Rani,
Jyoti Vashishtha
},
title = { An Appraise of KNN to the Perfection },
journal = {
International Journal of Computer Applications
},
issue_date = { Jul 2017 },
volume = { 170 },
number = { 2 },
month = { Jul },
year = { 2017 },
issn = { 0975-8887 },
pages = {
13-17
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume170/number2/28041-2017914696/
},
doi = { 10.5120/ijca2017914696 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:17:23.807417+05:30
%A Pooja Rani
%A Jyoti Vashishtha
%T An Appraise of KNN to the Perfection
%J International Journal of Computer Applications
%@ 0975-8887
%V 170
%N 2
%P 13-17
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract
K-Nearest Neighbor (KNN) is highly efficient classification algorithm due to its key features like: very easy to use, requires low training time, robust to noisy training data, easy to implement. However, it also has some shortcomings like high computational complexity, large memory requirement for large training datasets, curse of dimensionality and equal weights given to all attributes. Many researchers have suggested various advancements and improvements in KNN to overcome these shortcomings. This paper appraising various advancements and improvements in KNN.
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Index Terms
Computer Science
Information Sciences
Keywords