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Sorry if this is obvious but I haven't been able to find it anywhere else. I'm using xgboost's importance() function to generate a matrix of information about the variables in a multinomial classification model. I know the "Gain" column indicates roughly how much each variable contributed to the model's predictions. But I don't have a sense for which direction that contribution was in.

For example, in glmnet's version of this function, there are positive and negative values for gain, so for a binary classification you can see what correlated strongly with each outcome, both 1 and 0. I'm sorting my input into five groups. Should I assume that a higher gain value is always correlated with a higher group number? What is correlated with low group numbers?

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  • $\begingroup$ You want partial dependence plots. $\endgroup$ – Matthew Drury Aug 26 '17 at 1:42
  • $\begingroup$ Sorry, can you elaborate on what you mean by that? I'm pretty new to this world. $\endgroup$ – data princess Aug 27 '17 at 5:04

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