The AFT loss function.
More...
#include <survival_util.h>
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| | AFTLoss (ProbabilityDistributionType dist_type) |
| | Constructor for AFT loss function. More...
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| double | Loss (double y_lower, double y_upper, double y_pred, double sigma) |
| | Compute the AFT loss. More...
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| double | Gradient (double y_lower, double y_upper, double y_pred, double sigma) |
| | Compute the gradient of the AFT loss. More...
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| |
| double | Hessian (double y_lower, double y_upper, double y_pred, double sigma) |
| | Compute the hessian of the AFT loss. More...
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◆ AFTLoss()
Constructor for AFT loss function.
- Parameters
-
| dist_type | Choice of probability distribution for the noise term in AFT |
◆ Gradient()
| double xgboost::common::AFTLoss::Gradient |
( |
double |
y_lower, |
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|
double |
y_upper, |
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|
double |
y_pred, |
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|
double |
sigma |
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) |
| |
Compute the gradient of the AFT loss.
- Parameters
-
| y_lower | Lower bound for the true label |
| y_upper | Upper bound for the true label |
| y_pred | Predicted label |
| sigma | Scaling factor to be applied to the distribution of the noise term |
◆ Hessian()
| double xgboost::common::AFTLoss::Hessian |
( |
double |
y_lower, |
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|
double |
y_upper, |
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|
double |
y_pred, |
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|
double |
sigma |
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) |
| |
Compute the hessian of the AFT loss.
- Parameters
-
| y_lower | Lower bound for the true label |
| y_upper | Upper bound for the true label |
| y_pred | Predicted label |
| sigma | Scaling factor to be applied to the distribution of the noise term |
◆ Loss()
| double xgboost::common::AFTLoss::Loss |
( |
double |
y_lower, |
|
|
double |
y_upper, |
|
|
double |
y_pred, |
|
|
double |
sigma |
|
) |
| |
Compute the AFT loss.
- Parameters
-
| y_lower | Lower bound for the true label |
| y_upper | Upper bound for the true label |
| y_pred | Predicted label |
| sigma | Scaling factor to be applied to the distribution of the noise term |
The documentation for this class was generated from the following file: