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http://dx.doi.org/10.5351/KJAS.2018.31.3.417

Comparison of the performance of classification algorithms using cytotoxicity data  

Yoon, Yeochang (Department of Information Security, Woosuk University)
Jeung, Eui Bae (Department of Veterinary Medicine, Chungbuk National University)
Jo, Na Rae (Department of Statistics, Chungbuk National University)
Ju, Su In (Department of Statistics, Chungbuk National University)
Lee, Sung Duck (Department of Statistics, Chungbuk National University)
Publication Information
The Korean Journal of Applied Statistics / v.31, no.3, 2018 , pp. 417-426 More about this Journal
Abstract
An alternative developmental toxicity test using mouse embryonic stem cell derived embryoid bodies has been developed. This alternative method is not to administer chemicals to animals, but to treat chemicals with cells. This study suggests the use of Discriminant Analysis, Support Vector Machine, Artificial Neural Network and k-Nearest Neighbor. Algorithm performance was compared with accuracy and a weighted Cohen's kappa coefficient. In application, various classification techniques were applied to cytotoxicity data to classify drug toxicity and compare the results.
Keywords
discriminant analysis; support vector machine; artificial neural network; k-nearest neighbors classification; weighted Cohen's kappa coefficient; cytotoxicity;
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