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Using KNN Method for Educational and Vocational Guidance

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International Journal of Computer Applications
© 2014 by IJCA Journal
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 and Mohamed El Harzli. Article: Using KNN Method for Educational and Vocational Guidance. International Journal of Computer Applications 100(12):24-30, August 2014. Full text available. BibTeX

@article{key:article,
	author = {Essaid El Haji and Abdellah Azmani and Mohamed El Harzli},
	title = {Article: Using KNN Method for Educational and Vocational Guidance},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {100},
	number = {12},
	pages = {24-30},
	month = {August},
	note = {Full text available}
}

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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