Description Usage Arguments Details Value Methods (by class)
calcStats
calculates the performance of a deployed model.
1 2 3 4 5 6 7 8 9 |
object |
An |
aucSkip |
A logical scalar. Toggles whether to calculate area under the receiver operating characteristic curve. See Details. |
plotSkip |
A logical scalar. Toggles whether to plot the receiver operating characteristic curve. See Details. |
verbose |
A logical scalar. Toggles whether to print the results of model performance to console. |
For classification, if the argument aucSkip = FALSE
AND the ExprsArray
object was an ExprsBinary
object with at least one case and one control AND
ExprsPredict
contains a coherent @probability
slot, calcStats
will calculate classifier performance using the area under the receiver operating
characteristic (ROC) curve via the ROCR
package. Otherwise, calcStats
will calculate classifier performance traditionally using a confusion matrix.
Note that accuracies calculated using ROCR
may differ from those calculated
using a confusion matrix because ROCR
adjusts the discrimination threshold to
optimize sensitivity and specificity. This threshold is automatically chosen as the
point along the ROC which minimizes the Euclidean distance from (0, 1).
For regression, accuracy is defined the R-squared of the fitted regression. This
ranges from 0 to 1 for use with pl
and pipe
. Note that
the aucSkip
and plotSkip
arguments are ignored for regression.
Returns a data.frame
of performance metrics.
ExprsPredict
: Method to calculate performance for classification models.
RegrsPredict
: Method to calculate performance for continuous outcome models.
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