Early classification of multivariate temporal observations by extraction of interpretable shapelets

BMC Bioinformatics

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

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

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.

ISSN: 1471-2105