xgb.max_specificity: xgboost evaluation metric for maximum Specificity (True...
In Laurae2/Laurae: Advanced High Performance Data Science Toolbox for R
Description
Usage
Arguments
Value
Description
This function allows xgboost to use a custom thresholding method to maximize the Specificity (True Negative Rate) You can use this function via eval_metric. It leaks memory over time, but it can be reclaimed using gc().
Usage
1
xgb.max_specificity(pred, dtrain)
Arguments
pred
Type: numeric. The predictions.
dtrain
Type: xgb.DMatrix. The training data.
Value
The maximum Specificity (True Negative Rate) for binary data.
Laurae2/Laurae documentation built on May 8, 2019, 7:59 p.m.
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Description Usage Arguments Value
Description
This function allows xgboost to use a custom thresholding method to maximize the Specificity (True Negative Rate) You can use this function via eval_metric. It leaks memory over time, but it can be reclaimed using gc().
Usage
1 | xgb.max_specificity(pred, dtrain)
|
Arguments
pred |
Type: numeric. The predictions. |
dtrain |
Type: xgb.DMatrix. The training data. |
Value
The maximum Specificity (True Negative Rate) for binary data.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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