roc_curves: Functions for plotting roc curves
In PeerChristensen/autoMLviz: Plotting model performances from H2OAutoML objects
Description
Functions for plotting roc curves
Usage
1
roc_curves(H2OAutoML_object, plot = T, best = F, save_png = F,test_data,n_models = 5)
Arguments
H2OAutoML_object
An object containing multiple models trained in H2O.
plot
(Optional) Whether to plot the output. Default is TRUE.
best
(Optional) If set to TRUE, the function returns only the best model.
save_png
(Optional) Whether to save a .png with ggsave(). Default is FALSE.
test_data
The test data set.
n_models
(Optional) The number of trained models to include.
PeerChristensen/autoMLviz documentation built on Sept. 16, 2019, 1:19 p.m.
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Description
Functions for plotting roc curves
Usage
1 | roc_curves(H2OAutoML_object, plot = T, best = F, save_png = F,test_data,n_models = 5)
|
Arguments
H2OAutoML_object |
An object containing multiple models trained in H2O. |
plot |
(Optional) Whether to plot the output. Default is TRUE. |
best |
(Optional) If set to TRUE, the function returns only the best model. |
save_png |
(Optional) Whether to save a .png with ggsave(). Default is FALSE. |
test_data |
The test data set. |
n_models |
(Optional) The number of trained models to include. |
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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