MeasureValLoss: Validation Loss Measure
In pfistfl/distillery: Compress arbitrary mlr3 models into keras models
Description
Meta Information
Super class
Methods
Description
Validation Loss Measure
Validation Loss Measure
Meta Information
* Type: 'NA'
* Range: [0, Inf)
* Minimize: 'TRUE'
* Required prediction: 'response'
Super class
mlr3::Measure -> MeasureValLoss
Methods
Public methods
Inherited methods
Method new()
Creates a new measure that measures a keras learner's validation loss.
Usage
MeasureValLoss$new(id = "val_loss")
Arguments
idId of the measure
Creates a new instance of this [R6][R6::R6Class] class.
Method clone()
The objects of this class are cloneable with this method.
Usage
MeasureValLoss$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
pfistfl/distillery documentation built on April 17, 2021, 10 p.m.
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Description Meta Information Super class Methods
Description
Validation Loss Measure
Validation Loss Measure
Meta Information
* Type: 'NA' * Range: [0, Inf) * Minimize: 'TRUE' * Required prediction: 'response'
Super class
mlr3::Measure -> MeasureValLoss
Methods
Public methods
Inherited methods
Method new()
Creates a new measure that measures a keras learner's validation loss.
Usage
MeasureValLoss$new(id = "val_loss")
Arguments
idId of the measure Creates a new instance of this [R6][R6::R6Class] class.
Method clone()
The objects of this class are cloneable with this method.
Usage
MeasureValLoss$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
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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