How to create partial dependence plots for multinomial gbm in R?
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19 months ago
carina2817 ▴ 20

Hello,

I am trying to create partial dependence plots for my multinomial gbm predictions but I haven't been able to figure out how to produce the correct plots, the ones that I am getting have a single line instead of a line for every level of my response variable (in my case are 3 different species names). I have seen several examples but they require objects created with other packages (not gbm objects) and most of the examples don't include multinomial variables.

### gbm fit

gbm.fit.final<-readRDS(file = "gbm_fit_final1_organism.rds")


### getting table with variable importance

summary.gbm<-summary(
gbm.fit.final,
cBars = 10,
method = relative.influence,
las = 2)


The table looks like this:

      var   rel.inf
MA0356.1 22.641689
MA1071.1 21.707397
MA0311.1 16.010605
MA0210.1  7.249431
MA0271.1  4.958186


I used the following code to generate the partial dependence plot for the most important predictor variable:

gbm.fit.final %>%
partial(pred.var = "MA0356.1", n.trees = gbm.fit.final\$n.trees, grid.resolution = 100, prob=T) %>%
autoplot(rug = TRUE, train = motifs_train.100) +
scale_y_continuous()


motifs_train.100 is the training data that I used to create the gbm fit (gbm.fit.final), I am not sure if it is necessary to add the training data.

I got the following plot:

I would like to get a plot like this one (I think I need to get marginal probabilities):

I am very new to gbm package. I don't know if there is an argument of the function partial that I am omitting, or if there is a better function to do this. Any help would be appreciated. Thanks!

R GBM partial-dependence-plot PDP multinomial • 762 views