Description Usage Arguments Details Value
Trains and deploys models across a vast parameter search space.
1 2 |
array.train |
The |
array.valid |
The |
how |
A character string. The |
top |
A numeric scalar or character vector. A numeric scalar indicates
the number of top features that should undergo feature selection. A character vector
indicates specifically which features by name should undergo feature selection.
Set |
fold |
A numeric scalar. The number of folds for cross-validation.
Set |
aucSkip |
A logical scalar. Argument passed to |
plCV.acc |
A string. The performance metric to use. For example,
choose from "acc", "sens", "spec", "prec", "f1", "auc", or any of the
regression specific measures. Argument passed to |
verbose |
A logical scalar. Toggles whether to print to console. |
... |
Arguments passed to the |
plGrid
will build
and exprso-predict
for
each combination of parameters provided as additional arguments (...
).
When using plGrid
, supplying a numeric vector as the top
argument will train and deploy a model of each mentioned size for
each combination of parameters provided.
To skip validation set prediction, use array.valid = NULL
.
Either way, this function returns an ExprsPipeline-class
object which contains a summary of the build parameters and the models
themselves. The argument fold
controls inner-fold
cross-validation via plCV
. Use this to
select the best model unbiasedly.
An ExprsPipeline-class
object.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.