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Can the predicted function (equation) created by the regression learner toolbox be output?

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Scott on 21 Jul 2017
Commented: Scott on 21 Dec 2020
I have created a trained model GPR (RegressionGP,matern52) and have tested it using the predictFcn. Is there any way I can look at the final equation and associated parameters so that it can be incorporated into c++ code? Or do I have to find a similar c++ library or python machine learning library and try to duplicate my results (using a similar Gaussian Process Model)?
Scott on 21 Dec 2020
No. As Carl states below, I was able to get the final Hyperparameters, but not the equation(s). To incorporate into C++ code I duplicated the analysis in Python using scikit-learn using the aforementioned Hyperparameters and similar GPR model. It is very easy deploy and integrate Python machine learning models using "pickle" file and "SimpleXMLRPCServer" function. The matlab "coder" is another expensive Matlab add on that looked difficult to deploy with C++ code. My solution took a day or so. Scott.

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Answers (1)

Carl on 24 Jul 2017
You can extract the final parameters and equation from the GPR model's properties. See the following page:
You can obtain the values of beta, sigma, the hyperparameters, and other properties. Let me know if this doesn't provide what you are specifically looking for.
YiHao Zhu
YiHao Zhu on 6 Feb 2018
I want to use matlab coder to let my machine learning model in workspace to a function with c++ code.

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