Answered
Baysian Optimisation. Any way of increasing the sample size of candidates solutions to satisfy XConstraintFunction in bayesopt()?
Unfortunately the API doesn't allow that, but you can assign into the Options object once you have one. The bayesopt function cr...

7 years ago | 0

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Answered
Bug in bayesopt() function? Initial evaluation points table being incorrectly evaluated?
Hi Bob, You're running into a bug in bayesoptim.isInteger. You should be able to view that code by typing edit bayesoptim....

7 years ago | 0

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Answered
What is the difference between k-fold optimization and k-fold cross-validation in fitcecoc? Isn't it redundant?
I think it's fair to say that the returned model has been cross-validated, in the sense that it was chosen based on its cross-va...

7 years ago | 0

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Answered
Naive Bayes Posterior Probability
You can get the posterior probabilities from the second output of the predict method. See this page: http://www.mathworks.com/h...

7 years ago | 1

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Answered
Simulated annealing on a 3D matrix data set instead of a mathematical function?
Here's an illustration of how to do it with bayesopt. You would have your objective function call your external function (someho...

7 years ago | 0

Answered
bayesopt: change the default kernel / options
bayesopt doesn't have a way to do that from the command line, but you can do it by editing the code. The only place where fitrgp...

7 years ago | 3

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Using Bayesopt for TreeBagger Classification
Here's a variation that doesn't use a function-within-a-function. Maybe it's easier to understand: load fisheriris X = m...

7 years ago | 0

Answered
Using Bayesopt for TreeBagger Classification
How about something like this? Instead of crossval, it uses TreeBagger's ability to use the "out of bag" observations as validat...

7 years ago | 0

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bayesopt options pair: 'InitialX', {1x6} results in first cell-array entry taken as initial for all variables
Thanks for pointing this out. That's a bug, because bayesopt should not accept a cell array as the value for 'InitialX'. It expe...

7 years ago | 0

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Answered
Why it gives worse results when I use Genetic Algorithm for training NNs than when I use Back-propagation?
I think we should expect worse results with GA than with Backprop. Backpropagation training is a gradient-based minimization alg...

7 years ago | 0

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Answered
WHY CANNOT MATLAB POST SATISFACTORY EXAMPLES OF NN DESIGN USING GA ???
Greg, I posted an answer with corrected code in http://www.mathworks.com/matlabcentral/answers/100323 This is not a formal Do...

7 years ago | 0

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How can I use the Genetic Algorithm (GA) to train a Neural Network in Neural Network Toolbox?
The code posted by MathWorks Support Team on 18 Oct 2013 throws an error if you put it in a file and run it as-is, because the f...

7 years ago | 1

Answered
i want to optimize a neural network parameters by genetic algorithm and i get below code from matlab support, but the result is very poor even for a very simple function. how can i improve the result and is there any better code for my porpuse?
In the code you posted, mse_test is not calculating mean squared error. Here is a corrected version that seems to work fine. Pas...

7 years ago | 0

Answered
How to send a big data (loaded into datastore object) to a classifier in Matlab?
I think you need to pass tall arrays or a tall table to fitcnb. See the documentation here: http://www.mathworks.com/help/stats/...

7 years ago | 0

Answered
Finding optimal regression tree using hyperparameter optimization
My guess is that your first run was worse because it was not run for enough iterations. The default MaxObjectiveEvaluations is 3...

7 years ago | 1

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Answered
prediction without prior fitting in GPR
Set the initial parameter values and also pass 'FitMethod','None' http://www.mathworks.com/help/stats/fitrgp.html?searchHighl...

7 years ago | 0

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Answered
how to group data points in matrix
out = [A floor(A/5)]

7 years ago | 0

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How do I change the properties of a model object, when the object is generated by a toolbox?
I think the properties you want to set are 'protected' which means that only methods of the class or subclasses can set them. Th...

7 years ago | 0

Answered
How to get optimal tree when using random forest method
You could also try to find the best ensemble like this: fitcensemble(meas,species,'OptimizeHyperparameters','all') This ...

7 years ago | 0

Answered
How to use Bayesian Optimization?
You need to pass Y into oobErrRF. Change its first line to function oobErr = oobErrRF(params,X,Y) And change the call on...

7 years ago | 0

Answered
How to train a Naive Bayes classifier?
How about this? % Make a synthetic dataset STE = rand(84,1)*20; ZCR = randi(900,84,1); Category = [repmat({'unvoic...

7 years ago | 0

Answered
What do the Distribution Parameters of fitcnb mean?
Here is the doc page for them: <http://www.mathworks.com/help/stats/classificationnaivebayes-class.html#property_d0e141114>

7 years ago | 0

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Answered
Classification problem parsed as regression problem when Split Criterion is supplied to fitcensemble
Thanks, I now see cases succeeding with 'GentleBoost' and 'gdi' together. This is a bug in the search space for hyperparamete...

7 years ago | 1

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Answered
How to best do cross-validation using fitensemble?
It doesn't make any difference in the models. The only difference is that with the first method you also get a single model trai...

7 years ago | 0

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Answered
Change objective function for hyperparameter optimization in regression ensembles
'fitrensemble' doesn't support MAE, but you can use 'TreeBagger' to do what you want. TreeBagger fits a random forest and suppor...

7 years ago | 1

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Answered
how to use cross-validation in fitrgp
Briefly: The first command specifies a holdout proportion for fitting a single model. The second command specifies the holdout p...

7 years ago | 3

Answered
How to set arguments of 'fitrgp' while using 'bayesopt'?
You're right that bayesopt doesn't provide an interface for that. If you're willing to modify a source code file it can be done ...

7 years ago | 0

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Answered
Why does Support Vector Regression (fitrsvm) optimization result in poor performance ?
Maybe it's because the optimized SVR uses the default kernel function, which is 'linear'. If you include 'KernelFunction','gauss...

8 years ago | 0

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Answered
Hyper-parameter optimization for a custom kernel SVR with Bayesian optimization?
You'll need to use the bayesopt function to do that. There is an example of support vector classification on this page: http://w...

8 years ago | 0

Answered
Optimization with continuous/integer parameters and constraints
The bayesopt function in the Statistics & Machine Learning Toolbox release R2016b can handle all of these problems. The trick...

8 years ago | 0