Showing Predictor "MTLSAPaper_NSBCD"

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Test to see if we can run NSBCD dataset with 115 instances and 549 features (MTLSA paper claims that PSSP couldn't run high-dimensional data)

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Cross-validation results
5-Fold Cross-Validation Statistics*
Measure PSSP Predictor (median) PSSP Predictor (mean) K-M Predictor
Concordance Index0.75 ± 0.070.75 ± 0.070.5 ± 0.0
Hinged L1 Loss13.6 ± 2.7215.5 ± 1.42
Uncensored L1 loss33.41 ± 9.3258.66 ± 6.734.67 ± 4.39
Marginal L1 Loss33.35 ± 5.1551.03 ± 7.3222.01 ± 2.3
Marginal L2 LossN / A
Hinged L1 Log-Loss0.39 ± 0.070.5 ± 0.060.44 ± 0.03
Uncensored L1 Log-Loss1.03 ± 0.21.49 ± 0.121.17 ± 0.12
Marginal L1 Log-Loss0.71 ± 0.120.94 ± 0.110.6 ± 0.05
Log-Likelihood Loss1.54 ± 0.24
D-calibration χ2 statistics6.43 ± 2.539.61 ± 5.93
D-calibration χ2 p-value0.99 ± 0.020.86 ± 0.25
*Mean value ± standard deviation.


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