# summary.gbm

From gbm v0.6
0th

Percentile

##### Summary of a gbm object

Computes the relative influence of each variable in the gbm object.

Keywords
hplot
##### Usage
summary.gbm(object,
cBars=min(10,object$cCols), n.trees=object$n.trees,
plotit=TRUE,...)
##### Arguments
object
a gbm object created from an initial call to gbm.
cBars
the number of bars to plot. Only the variables with the cBars largest relative influence will appear in the barplot.
n.trees
the number of trees used to generate the plot. Only the first n.trees trees will be used.
plotit
an indicator as to whether the plot is generated.
...
other arguments passed to the plot function.
##### Details

Details to come later

##### Value

• Returns a data frame where the first component is the variable name and the second is the computed relative influence, normalized to sum to 100.

##### References

J.H. Friedman (2001). "Greedy Function Approximation: A Gradient Boosting Machine," Annals of Statistics 29(4).

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