augment.caretx: Predictions with explanatory variables.
In PiotrTymoszuk/caretExtra: Extra functionality for predictions and quality control of caret models
augment.caretx R Documentation
Predictions with explanatory variables.
Description
The augment() method for caretx objects derives the
predictions for the training, resample (CV), and, optionally, test
data set appended with the explanatory variables.
Usage
## S3 method for class 'caretx'
augment(x, newdata = NULL, ...)
Arguments
x
a caretx object.
newdata
an optional data frame with the test data.
...
extra arguments, currently none.
Value
a list of data frames. Each of them contains the
observation number (.observation),
resample ID (only for resample/CV, .resample),
outcome (.outcome), fitted values/classes (.fitted).
For classification models, class assignment probabilities are returned
as well (columns named after levels of the .outcome variable).
PiotrTymoszuk/caretExtra documentation built on Oct. 15, 2023, 10:03 p.m.
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| augment.caretx | R Documentation |
Predictions with explanatory variables.
Description
The augment() method for caretx objects derives the
predictions for the training, resample (CV), and, optionally, test
data set appended with the explanatory variables.
Usage
## S3 method for class 'caretx'
augment(x, newdata = NULL, ...)
Arguments
x |
a |
newdata |
an optional data frame with the test data. |
... |
extra arguments, currently none. |
Value
a list of data frames. Each of them contains the
observation number (.observation),
resample ID (only for resample/CV, .resample),
outcome (.outcome), fitted values/classes (.fitted).
For classification models, class assignment probabilities are returned
as well (columns named after levels of the .outcome variable).
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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