This measure specializes Measure for classification problems:
task_type is set to
Possible values for
Default classification measures:
Creates a new instance of this R6 class.
Identifier for the new instance.
TRUE if good predictions correspond to small values,
FALSE if good predictions correspond to large values.
If set to
NA (default), tuning this measure is not possible.
How to average multiple Predictions from a ResampleResult.The default,
"macro", calculates the individual performances scores for each Prediction and then uses the
function defined in
$aggregator to average them to a single number.If set to
"micro", the individual Prediction objects are first combined into a single new Prediction object which is then used to assess the performance.
The function in
$aggregator is not used in this case.
Function to aggregate individual performance scores
x is a numeric vector.
NULL, defaults to
Prediction sets to operate on, used in
aggregate() to extract the matching
predict_sets from the ResampleResult.
Multiple predict sets are calculated by the respective Learner during
Must be a non-empty subset of
If multiple sets are provided, these are first combined to a single prediction object.
String in the format
[pkg]::[topic] pointing to a manual page for this object.
The referenced help package can be opened via method