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 |