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How to obtain generalised linear model equation using SVM (radial kernel)?

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Suppose i am trying to use logistic regression to predict probabilities, i have two independent variables (P and Q) and a binary dependent variable C. I will use logistic regression to calculate individual coefficients of P and Q (let us say m and n respectively) plus a constant(let us say b). The fundamental equation of generalized linear model will be (mP + nQ + b). I can now use this equation to calculate probabilities.

Similarly, if I am using support vector, how am I going to get this kind of generalised linear model equation? I have used scikit in Python and also R, all i get is total number of support vectors and their values and value for (alpha (i) x X(i)). I need to assign individual weight to the two variable P and Q plus bias (b) so that I could use this equation as a generaised linear model. I am getting the constant term from Python but how am i suppose to generate coefficients of P and Q using SVM radial kernel? Therefore I was wondering if there is some way I could assign weights to my two variables and create the linear function which i could use. I would be very grateful for an explanation.

python scikit-learn predictive-modeling svm libsvm

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asked 6 mins ago

Alejandro Alejandro

61

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Alejandro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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0

$begingroup$

Suppose i am trying to use logistic regression to predict probabilities, i have two independent variables (P and Q) and a binary dependent variable C. I will use logistic regression to calculate individual coefficients of P and Q (let us say m and n respectively) plus a constant(let us say b). The fundamental equation of generalized linear model will be (mP + nQ + b). I can now use this equation to calculate probabilities.

Similarly, if I am using support vector, how am I going to get this kind of generalised linear model equation? I have used scikit in Python and also R, all i get is total number of support vectors and their values and value for (alpha (i) x X(i)). I need to assign individual weight to the two variable P and Q plus bias (b) so that I could use this equation as a generaised linear model. I am getting the constant term from Python but how am i suppose to generate coefficients of P and Q using SVM radial kernel? Therefore I was wondering if there is some way I could assign weights to my two variables and create the linear function which i could use. I would be very grateful for an explanation.

python scikit-learn predictive-modeling svm libsvm

share

asked 6 mins ago

Alejandro Alejandro

61

New contributor

Alejandro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

Suppose i am trying to use logistic regression to predict probabilities, i have two independent variables (P and Q) and a binary dependent variable C. I will use logistic regression to calculate individual coefficients of P and Q (let us say m and n respectively) plus a constant(let us say b). The fundamental equation of generalized linear model will be (mP + nQ + b). I can now use this equation to calculate probabilities.

Similarly, if I am using support vector, how am I going to get this kind of generalised linear model equation? I have used scikit in Python and also R, all i get is total number of support vectors and their values and value for (alpha (i) x X(i)). I need to assign individual weight to the two variable P and Q plus bias (b) so that I could use this equation as a generaised linear model. I am getting the constant term from Python but how am i suppose to generate coefficients of P and Q using SVM radial kernel? Therefore I was wondering if there is some way I could assign weights to my two variables and create the linear function which i could use. I would be very grateful for an explanation.

python scikit-learn predictive-modeling svm libsvm

share

asked 6 mins ago

Alejandro Alejandro

61

New contributor

Alejandro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

share

asked 6 mins ago

Alejandro Alejandro

61

New contributor

Alejandro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share

asked 6 mins ago

Alejandro Alejandro

61

New contributor

Alejandro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 6 mins ago

Alejandro Alejandro

61

New contributor

Alejandro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 6 mins ago

Alejandro Alejandro

61