optimizableVariable - Variable description for bayesopt or other
optimizers - MATLAB ([original](https://in.mathworks.com/help/stats/optimizablevariable.html)) ([raw](?raw))
Variable description for bayesopt
or other optimizers
Description
Create variables for optimizers.
Creation
Syntax
Description
variable = optimizableVariable(`Name`,`Range`)
creates a variable with the specified name and range of values.
variable = optimizableVariable(`Name`,`Range`,Name,Value)
sets properties using name-value arguments. For example, optimizableVariable('xvar',[1 1000],'Type','integer')
creates an integer variable from 1 to 1000. You can specify multiple name-value arguments. Enclose each property name in quotes.
Properties
Variable name, specified as a character vector or string scalar. The name must be unique, meaning different from those of other variables in the optimization.
Note
- There are two names associated with an
optimizableVariable
:- The MATLABĀ® workspace variable name
- The name of the variable in the optimization
For example,
xvar = optimizableVariable('spacevar',[1,100]);xvar
is the MATLAB workspace variable, and'spacevar'
is the variable in the optimization.
Use these names as follows: - Use
xvar
as an element in the vector of variables you pass tobayesopt
. For example,
results = bayesopt(fun,[xvar,tvar]) - Use
'spacevar'
as the name of the variable in the optimization. For example, in an objective function,
function objective = mysvmfun(x,cdata,grp)
SVMModel = fitcsvm(cdata,grp,'KernelFunction','rbf',...
'BoxConstraint',x.spacevar,...
'KernelScale',x.tvar);
objective = kfoldLoss(crossval(SVMModel));
Example: 'X1'
Data Types: char
| string
Variable range, specified as a 2-element finite increasing real vector, or as a string array or cell array of category names:
- For real or integer variables,
Range
gives the lower bound and upper bound of that variable. - For categorical variables,
Range
gives the possible values.
Example: [-10,1]
Example: {'red','blue','black'}
Data Types: double
| string
| cell
Variable type, specified as 'real'
(real variable),'integer'
(integer variable), or'categorical'
(categorical variable).
Note
The MATLAB data type of both 'real'
and'integer'
variables is the standard double-precision floating point number. The data type of'categorical'
variables is categorical. So, for example, to read a value of a categorical variable named'colorv'
in a table of variables namedx
, use the commandchar(x.colorv)
. For an example, see the objective function in Custom Output Functions.
Example: 'Type','categorical'
Transform applied to the variable, specified as 'none'
(no transform) or 'log'
(logarithmic transform).
For 'log'
, the variable must be a positive real variable ('Type','real'
) or a nonnegative integer variable ('Type','integer'
). The software searches and models the variable on a log scale.
Example: 'Transform','log'
Indication to use variable in optimization, specified astrue
(use the variable) or false
(do not use the variable).
Example: 'Optimize',false
Data Types: logical
Note
You can use dot notation to change the following properties after creation.
Range
of real or integer variables. For example,
xvar = optimizableVariable('x',[-10,10]);
% Modify the range:
xvar.Range = [1,5];Type
between'integer'
and'real'
. For example,Transform
of real or integer variables between'log'
and'none'
. For example,
You can use this flexibility, for example, to tweak an optimization that you want to continue. Update the range or transform using dot notation and then callresume.
Object Functions
bayesopt | Select optimal machine learning hyperparameters using Bayesian optimization |
---|
Examples
Real variable from 0 to 1:
var1 = optimizableVariable('xvar',[0 1])
var1 = optimizableVariable with properties:
Name: 'xvar'
Range: [0 1]
Type: 'real'
Transform: 'none'
Optimize: 1
Integer variable from 0 to 1000 on a log scale:
var2 = optimizableVariable('ivar',[0 1000],'Type','integer','Transform','log')
var2 = optimizableVariable with properties:
Name: 'ivar'
Range: [0 1000]
Type: 'integer'
Transform: 'log'
Optimize: 1
Categorical variable of rainbow colors:
var3 = optimizableVariable('rvar',{'r' 'o' 'y' 'g' 'b' 'i' 'v'},'Type','categorical')
var3 = optimizableVariable with properties:
Name: 'rvar'
Range: {'r' 'o' 'y' 'g' 'b' 'i' 'v'}
Type: 'categorical'
Transform: 'none'
Optimize: 1
Version History
Introduced in R2016b