[SOLVED] Weights in a weka random forest model
New Altair Community Member
Updated by Jocelyn
First off, apologies if any of this sounds ignorant. I'd appreciate any insight, as I am making the transition from working with SPSS doing logistic regression prediction models to exploring other types of models in rapidminer.
In a logistic regression model you are given the coefficients, which can be used to approximate the importance of each element in the model. You can use them to tell whether, for example, predictor A is 3x as important as predictor B. My management has gotten used to seeing that type of information.
I am now working with rapidminer and have hit upon a weka random forest model that is substantially better at predicting (per 10-fold x-validation testing) than my original logistic regression model. However my management is asking for some comparable indicator of comparative importance. Can anyone suggest an appropriate way to get that type of information? What objects? What should I be looking for?
Rebecca
In a logistic regression model you are given the coefficients, which can be used to approximate the importance of each element in the model. You can use them to tell whether, for example, predictor A is 3x as important as predictor B. My management has gotten used to seeing that type of information.
I am now working with rapidminer and have hit upon a weka random forest model that is substantially better at predicting (per 10-fold x-validation testing) than my original logistic regression model. However my management is asking for some comparable indicator of comparative importance. Can anyone suggest an appropriate way to get that type of information? What objects? What should I be looking for?
Rebecca