Showing Predictor "NACD_L2MargLoss"

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from V Baracos

[Trained to optimize Log Likelihood, with L1 regularization ]

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Regularization: L2	Tuning Score: avg marginal l1-loss
Time Points: 50	Tune Parameters: true
Feature Selection: false	Include Sibling Features: false
Standardize: true	Run Cross-Validation: true
Objective Function: l2 marginal loss	Marginal Loss Type: weighted
Use pre-defined Fold: No

Results
Start Time: 2017-05-09 15:32:04 -0600	Used Time: 5 minutes
Label Name: SURVIVAL	C Parameter: 0.1
PSSP model: mtlr_model_file2637.mtlr	Version: 0.0.2

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Cross-validation results

5-Fold Cross-Validation Statistics*
Measure	PSSP Predictor (median)	PSSP Predictor (mean)	K-M Predictor
Concordance Index	0.76 ± 0.01	0.76 ± 0.01	0.5 ± 0.0
Hinged L1 Loss	13.76 ± 0.86		13.28 ± 0.05
Uncensored L1 loss	13.64 ± 0.51	12.83 ± 0.46	12.18 ± 0.05
Marginal L1 Loss	20.01 ± 1.31	16.23 ± 0.51	20.96 ± 0.16
Marginal L2 Loss	29.7 ± 1.74		27.14 ± 0.29
Hinged L1 Log-Loss	0.92 ± 0.07	0.62 ± 0.02	0.79 ± 0.01
Uncensored L1 Log-Loss	1.01 ± 0.05	0.89 ± 0.02	0.97 ± 0.01
Marginal L1 Log-Loss	1.11 ± 0.09	0.79 ± 0.02	1.02 ± 0.01
Log-Likelihood Loss	8.97 ± 0.86
D-calibration χ² statistics	223.74 ± 56.38		0.97 ± 0.12
D-calibration χ² p-value	0.0 ± 0.0		1.0 ± 0.0

*Mean value ± standard deviation.

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