The week's pick
Reseach Article
Using KNN Method for Educational and Vocational Guidance
by
Essaid El Haji,
Abdellah Azmani,
Mohamed El Harzli
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 100 - Number 12 |
| Year of Publication: 2014 |
| Authors: Essaid El Haji, Abdellah Azmani, Mohamed El Harzli |
10.5120/17578-8335
|
Essaid El Haji, Abdellah Azmani, Mohamed El Harzli . Using KNN Method for Educational and Vocational Guidance. International Journal of Computer Applications. 100, 12 ( August 2014), 24-30. DOI=10.5120/17578-8335
@article{
10.5120/17578-8335,
author = {
Essaid El Haji,
Abdellah Azmani,
Mohamed El Harzli
},
title = { Using KNN Method for Educational and Vocational Guidance },
journal = {
International Journal of Computer Applications
},
issue_date = { August 2014 },
volume = { 100 },
number = { 12 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = {
24-30
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume100/number12/17578-8335/
},
doi = { 10.5120/17578-8335 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:29:48.101386+05:30
%A Essaid El Haji
%A Abdellah Azmani
%A Mohamed El Harzli
%T Using KNN Method for Educational and Vocational Guidance
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 12
%P 24-30
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This paper presents a decision support tool for educational and vocational guidance, based on the supervised classification method k-nearest neighbors (KNN). This method consists in determining, for each new observation to be classified, the list of nearest neighbors of the observations already classified. The use of the KNN method requires choosing a distance and the most classical one is the Euclidean distance. In the context of this work, two functions were tested to measure resemblance as far as similarity and dissimilarity are concerned.
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Index Terms
Computer Science
Information Sciences
Keywords