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Table 1 Performance of classifiers on training and test sets

From: Impact of image segmentation on high-content screening data quality for SK-BR-3 cells

  5-fold cross-validation   Independent test set
Classifier Features Accuracy Accuracy
LDA 19 79.5% 78.7%
SVM-linear 25 80.1% 78.9%
SVM-RBF 7 81.5% 80.9%
  1. LDA, SVM (linear kernel), and SVM (radial basis kernel) classifiers were first assessed by 5-fold cross validation accuracy for a range of model sizes. The minimum number of features that gave a cross-validation accuracy within one SEM of the maximum accuracy for all model sizes was determined, and is shown in the first column of the table, along with the corresponding cross-validation accuracy. Once the optimal parsimonious model size (number of features) was determined from cross-validation, the classifiers were applied to the independent test set; the test-set accuracy is shown in the right-most column of the table.