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. 2014 May 16;15:145. doi: 10.1186/1471-2105-15-145

Table 5.

The contribution of transcriptomic features in improving the classification accuracy

Dataset All
Genomic
Transcriptomic
IGR, CuScore
IGR, CuScore
Features
Features
and IGR-Expr
and Diff-Expr
NN RF SVM NN RF SVM NN RF SVM NN RF SVM NN RF SVM
PG1
0.98
0.97
0.97
0.9
0.89
0.9
0.89
0.87
0.88
0.96
0.96
0.96
0.91
0.94
0.87
PG2
0.99
0.99
0.97
0.95
0.95
0.92
0.9
0.9
0.91
0.97
0.97
0.96
0.97
0.96
0.97
PG3
0.98
0.97
0.97
0.95
0.94
0.9
0.92
0.89
0.91
0.96
0.95
0.95
0.96
0.95
0.96
HS2336 0.95 0.97 0.97 0.86 0.86 0.86 0.89 0.88 0.89 0.94 0.96 0.95 0.88 0.89 0.88

Four subsets of features have been tested and compared by the corresponding accuracy values. The first column reports the accuracy results with all the features. The next two columns show the accuracy values achieved, respectively, with genomic and transcriptomic features. Finally, the last two columns display the improvement, in classification accuracy, obtained combining one transcriptomic feature to the two genomic features.