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

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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)?
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Sadaf Batool
Sadaf Batool il 19 Dic 2020
Modificato: Sadaf Batool il 19 Dic 2020
Hey @Scott,
Were you able to get the equation from the trained model?
Scott
Scott il 21 Dic 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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Risposte (1)

Carl
Carl il 24 Lug 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.
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YiHao Zhu
YiHao Zhu il 6 Feb 2018
After I use regression learner and export the model to the workspace, I can use it to train my new data in matlab. But when I try to use matlab coder to develop c++ code, it fail. Really need a video to show me how to do it.
YiHao Zhu
YiHao Zhu il 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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