Classification performance for making decisions about products missing from the shelf
Authors: Papakyriakopoulos, Dimitrios 
Doukidis, Georgios 
Issue Date: 18-Aug-2011
Journal: Advances in Decision Sciences 
Volume: 2011
Abstract: 
The out-of-shelf problem is among the most important retail problems. This work employs two different classification algorithms, C4.5 and nÄive Bayes, in order to build a mechanism that makes decisions about whether a product is available on a retail store shelf or not. Following the same classification methods and feature spaces, we examined the classification performance of the algorithms in fou...
ISSN: 2090-3367
2090-3359
DOI: 10.1155/2011/515978
URI: https://uniwacris.uniwa.gr/handle/3000/2159
Type: Article
Department: Department of Business Administration 
School: School of Administrative, Economics and Social Sciences 
Affiliation: University of West Attica (UNIWA) 
Appears in Collections:Articles / Άρθρα

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