Accurate multi-criteria decision making methodology for recommending machine learning algorithm

Citation data:

Expert Systems with Applications, ISSN: 0957-4174, Vol: 71, Page: 257-278

Publication Year:
2017
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Citations 9
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DOI:
10.1016/j.eswa.2016.11.034
Author(s):
Rahman Ali; Sungyoung Lee; Tae Choong Chung
Publisher(s):
Elsevier BV
Tags:
Engineering; Computer Science
article description
Manual evaluation of machine learning algorithms and selection of a suitable classifier from the list of available candidate classifiers, is highly time consuming and challenging task. If the selection is not carefully and accurately done, the resulting classification model will not be able to produce the expected performance results. In this study, we present an accurate multi-criteria decision making methodology (AMD) which empirically evaluates and ranks classifiers’ and allow end users or experts to choose the top ranked classifier for their applications to learn and build classification models for them.