I have 33 variables my dataset, I need to omit some less significant features then, which is the "best suitable feature selection method " for the Ordinal Logistic Regression?
In some problems, data scientists use Logistic regression to decide what are the important features(Independent variables) that have higher effect on the target(Dependent variable).
Because logistic regression itself will map variables to variable Importance level. Which may help you deciding which features to use in production. you can search for "logistic regression variable importance" to know more about this.
- You can also use random forests (Decision trees) and visualize what variables are used in early splits, these variables will have higher effect on dependent variable too. then you can pick n features based on your preference.