Skip to main content

Table 2 Evaluation of the MSD method on the drug response datasets using a subset of genes that gives the highest accuracy

From: Early classification of multivariate temporal observations by extraction of interpretable shapelets

Dataset genes Accuracy Relative accuracy Coverage Earliness F 1
H3N2 Top 11 genes 80.00 87.50 88.89 64.29 0.4938
HRV RSAD2 71.43 75.00 100 38.89 0.6587
Baranzini3A Caspase 10 75.00 76.00 100 45.45 0.6316
Baranzini3B Caspase 2 , Caspase 3 75.00 76.19 100 44.05 0.6409
Baranzini6 Caspase 10 , IL-4Ra 75.00 76.00 100 43.45 0.6448
Lin9 Caspase 2, Caspase 3, Jak2 81.82 82.61 100 43.43 0.6689
  1. The MSD method has been evaluated on all combinations of the genes on 4 datasets. The accuracy of the classifier is improved than using all genes. For example, the performance of MSD method on the Lin9 dataset is improved significantly from 68% to 82% when using only 3 genes instead of 9 genes.