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Consolidated results

Comparison of results

Number Description Initialization.method Correction Training.size Test.size K.of.training K.of.testing P.value.of.KMC.in.training P.value.of.KMC.in.testing Predictive.C.Index Recovery.C.Index
1 Original SBC implementation in the Verhaak samples present in the TCGA-GBM data set K-means None 80 80 4 6 6.406e-14 1.868e-02 0.573 0.744
2 Original SBC implementation in the TCGA-GBM dataset K-means Karnofsky Index correction 160 261 4 4 3.197e-06 1.704e-03 0.478 0.683
3 ssGSEA on KEGG pathways for feature engineering K-means Karnofsky Index correction 160 261 4 3 2.205e-01 6.616e-02 0.509 0.469
4 ssGSEA Oncogenic gene sets for feature engineering K-means Karnofsky Index correction 160 261 4 4 3.958e-04 2.667e-02 0.501 0.634
5 ssGSEA on the Canonical Pathways for feature engineering K-means Karnofsky Index correction 160 261 4 2 6.808e-03 1.157e-01 0.524 0.604
6 Penalised Cox model on the Oncogenic gene sets for feature engineering K-means Karnofsky Index correction 160 261 5 3 0.000e+00 7.452e-02 0.530 0.966
7 PAFT the Oncogenic gene sets for feature engineering K-means Karnofsky Index correction 160 261 4 4 0.000e+00 1.806e-02 0.528 0.959
8 Block HSIC-Lasso for feature selection K-means Karnofsky Index correction 160 261 4 4 1.078e-05 4.701e-02 0.565 0.698