Timotius I, Miaou SG (2010)
Publication Language: English
Publication Type: Conference contribution, Original article
Publication year: 2010
Publisher: IEEE
Pages Range: 1244 - 1251
Conference Proceedings Title: International Conference on Audio, Language and Image Processing (ICALIP 2010)
ISBN: 978-1-4244-5856-1
URI: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5685124
DOI: 10.1109/ICALIP.2010.5685124
Classifier performance measurement is essential in the development and analysis of classification algorithms. This paper proposes a new measurement approach that can be used generally for the balanced and imbalanced data set, can reflect the random guessing behavior perfectly, and can be used easily in cost-sensitive classification and multiple-class classification.
APA:
Timotius, I., & Miaou, S.-G. (2010). Arithmetic Means of Accuracies: A Classifier Performance Measurement for Imbalanced Data Set. In International Conference on Audio, Language and Image Processing (ICALIP 2010) (pp. 1244 - 1251). Shanghai, CN: IEEE.
MLA:
Timotius, Ivanna, and Shaou-Gang Miaou. "Arithmetic Means of Accuracies: A Classifier Performance Measurement for Imbalanced Data Set." Proceedings of the International Conference on Audio, Language and Image Processing (ICALIP 2010), Shanghai IEEE, 2010. 1244 - 1251.
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