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Assessing the significance of predictors in SVM and Ordinal Logistic Regression

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Roohollah Milimonfared
Roohollah Milimonfared on 30 Aug 2017
Commented: Jim Joy on 1 Sep 2017
Ordinal Logistic Regression allows comparison of predictors with respect to each other according to their p-value. Also, within each predictor, it is possible to quantify the influence of its variation on the outcome variable (i.e. category or class). For categorical predictors, you will be able to interpret the odds that one group had a higher or lower value on the outcome variable compared to another group. For continuous variables, you will be able to interpret how a single unit increase or decrease in that variable was associated with the odds of the outcome variable having a higher value. My question is whether from an SVM model, such information about the influence of predictor variables on the outcome variable can be acquired.

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Jim Joy
Jim Joy on 1 Sep 2017
Hi Roohollah,
Could you please clarify what you mean by the 'influence' of the particular variables?
For example, are you using SVM for classification or regression? If you are using it for regression, would you like to know the gradient of the model with respect to each predictor variable?
Thanks, Jim

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