Table 2.

The participants that submitted models for every endpoint (original and swap) in the MAQC-II study, and the classification methods used

Code	Name	Classification algorithm(s) used
CAS	Chinese Academy of Sciences	Naïve Bayes, Support Vector Machine
CBC	CapitalBio Corporation, China	k-Nearest Neighbor, Support Vector Machine
Cornell	Weill Medical College of Cornell University	Support Vector Machine
FBK	Fondazione Bruno Kessler, Italy	Discriminant Analysis, Support Vector Machine
GeneGo	GeneGo, Inc.	Discriminant Analysis, Random Forest
GHI	Golden Helix, Inc.	Classification Tree
GSK	GlaxoSmithKline	Naïve Bayes
NCTR	National Center for Toxicological Research, FDA	k-Nearest Neighbor, Naïve Bayes, Support Vector Machine
NWU	Northwestern University	k-Nearest Neighbor, Classification Tree, Support Vector Machine
SAI	Systems Analytics, Inc.	Discriminant Analysis, k-Nearest Neighbor, Machine Learning, Support Vector Machine, Logistic Regression
SAS	SAS Institute, Inc.	Classification Tree, Discriminant Analysis, Logistic Regression, Partial Least Squares, Support Vector Machine
Tsinghua	Tsinghua University, China	Classification Tree, k-Nearest Neighbor, Recursive Feature Elimination, Support Vector Machine
UIUC	University of Illinois, Urbana-Champaign	Classification Tree, k-Nearest Neighbor, Naïve Bayes, Support Vector Machine
USM	University of Southern Mississippi	Artificial Neural Network, Naïve Bayes, Sequential Minimal Optimization, Support Vector Machine
ZJU	Zejiang University, China	k-Nearest Neighbor, Nearest Centroid