MATLAB: How to develop regression function (Mathmatical form) from trained model using regression learner

machine learningsupport vector regresssion

How to extract regression function in term of mathmatical form (or tool or excel sheet) from trained model using regression learner (Support Vector Regression).

Best Answer

In case of support vector machines(both for classification and regression), the score function/regression function might not be in terms of input predictors, hence it might not be possible to get the regression function. The coefficients can be obtained using

trainedModel.RegressionSVM

As a workaround, you can use other regression techniques such as linear regression, which derive output in terms of predictors.

Related Solutions

MATLAB: Regression

Here is an example:

x = (1:20)';
y = 2 + 3*x + 7*rand(20,1);
model = fit(x,y,'poly1')
figure
plot(model,x,y)

The plot command here is an "overloaded" method for cfit objects (the output of the fit command). The documentation is here: http://www.mathworks.com/help/toolbox/curvefit/plot.html

MATLAB: Classification Learner App :: Logistic Regression – Decision Making

Hi Tarunima,

Classification Learner App is just an UI, interior the same Deep learning algorithm has been implemented. If you are using logistic regression the default setting uses “fitglm” function as you mentioned, this function just tries to model the probability of certain class or events existing such as pass/fail. The class with more probability assigned as the predicted class. If you are interested more in finding the algorithm behind it, you can check out following link.

https://www.mathworks.com/help/stats/fitglm.html#mw_0fd53dcd-2470-4661-8735-434f6ef41591

I hope this helps you.

Best Answer

Related Solutions

MATLAB: Regression

MATLAB: Classification Learner App :: Logistic Regression – Decision Making

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