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rgbm

Extracting the relative influence from a gbm.fit object

I am trying to extract the relative influence of each variable from a gbm.fit object but it is coming up with the error below:

       > summary(boost_cox, plotit = FALSE)
       Error in data.frame(var = object$var.names[i], rel.inf = rel.inf[i]) : 
       row names contain missing values

The boost_cox object itself is fitted as follows:

    boost_cox = gbm.fit(x = x,
                        y = y,
                        distribution="coxph",
                        verbose = FALSE,
                        keep.data = TRUE)

I have to use the gbm.fit function rather than the standard gbm function due to the large number of predictors (26k+)

Solution

  • I have solve this issue now myself.

    The relative.influence() function can be used and works for objects created using both gbm() and gbm.fit(). However, it does not provide the plots as in the summary() function.

    I hope this helps anyone else looking in the future.