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Table 2 Comparison with Other methods

From: A multi-omics supervised autoencoder for pan-cancer clinical outcome endpoints prediction

Methods OS DSS PFI DFI
SVM 0.6905
(±0.0108)
0.6927
(±0.0154)
0.6416
(±0.0119)
0.5950
(±0.0174)
DecisionTree 0.6973
(±0.0082)
0.6877
(±0.0199)
0.6503
(±0.0093)
0.5736
(±0.0276)
Naïve Bayes 0.6825
(±0.0110)
0.7139
(±0.0277)
0.6672
(±0.0074)
0.6631
(±0.0304)
kNN 0.7189
(±0.0086)
0.7134
(±0.0146)
0.6788
(±0.0095)
0.6488
(±0.0474)
RandomForest 0.7355
(±0.0082)
0.7449
(±0.0160)
0.6999
(±0.0134)
0.6621
(±0.0299)
AdaBoost 0.7297
(±0.0042)
0.7369
(±0.0219)
0.6831
(±0.0155)
0.6454
(±0.0254)
Multi-view Factorization
AutoEncoder [3]
0.766
(−)
0.724
(−)
MOSAE 0.7830
(±0.0081)
0.7870
(±0.0293)
0.7325
(±0.0123)
0.7061
(±0.0393)