Description Usage Arguments Details See Also Examples
A wrapper around the bwplot function in caret to visualize models even if models are trained using different metrics.
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models |
A list of models from ml_list function or manually combine finely tuned models from ml_tune or train function from caret package. |
metric |
A character, the metric of model performance, the available values are "ROC","Sens","Spec","Accuracy","Kappa". |
If the models contains metrics from c("ROC","Sens","Spec") and c("Accuracy","Kappa"), then it will plot two graphs. You could not plot the "ROC","Sens" or "Spec" value for a model if the model trained by using "Accuracy" or "Kappa", and vice versa.
To see how the list of models are generated ml_list
and ml_tune
.
The bwplot function is not documented on CRAN but you could see it on caret tutorial https://topepo.github.io/caret/model-training-and-tuning.html
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