R6_par_discretenum {comparer} | R Documentation |
R6 object for discrete numeric
Description
R6 object for discrete numeric
R6 object for discrete numeric
Details
Parameter with uniform distribution for hyperparameter optimization
Super class
comparer::par_hype
-> par_discretenum
Public fields
name
Name of the parameter, must match the input to 'eval_func'.
values
Values, discrete numeric
ggtrans
Transformation for ggplot, see ggplot2::scale_x_continuous()
Methods
Public methods
Method fromraw()
Function to convert from raw scale to transformed scale
Usage
R6_par_discretenum$fromraw(x)
Arguments
x
Value of raw scale
Method toraw()
Function to convert from transformed scale to raw scale
Usage
R6_par_discretenum$toraw(x)
Arguments
x
Value of transformed scale
Method generate()
Generate values in the raw space based on quantiles.
Usage
R6_par_discretenum$generate(q)
Arguments
q
In [0,1].
Method getseq()
Get a sequence, uniform on the transformed scale
Usage
R6_par_discretenum$getseq(n)
Arguments
n
Number of points. Ignored for discrete.
Method isvalid()
Check if input is valid for parameter
Usage
R6_par_discretenum$isvalid(x)
Arguments
x
Parameter value
Method convert_to_mopar()
Convert this to a parameter for the mixopt R package.
Usage
R6_par_discretenum$convert_to_mopar(raw_scale = FALSE)
Arguments
raw_scale
Should it be on the raw scale?
Method new()
Create a hyperparameter with uniform distribution
Usage
R6_par_discretenum$new(name, values)
Arguments
name
Name of the parameter, must match the input to 'eval_func'.
values
Numeric values, must be in ascending order
Method print()
Print details of the object.
Usage
R6_par_discretenum$print(...)
Arguments
...
not used
Method clone()
The objects of this class are cloneable with this method.
Usage
R6_par_discretenum$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
Examples
p1 <- R6_par_discretenum$new('x1', 0:2)
class(p1)
print(p1)