Description Usage Arguments Details Value See Also
Plots the model implied effect of 1 predictor for one outcome
1 2 3 |
x |
|
predictor.no |
index of the predictor variable |
response.no |
index of the response variable |
n.trees |
desired number of trees. Defaults to the minimum number of trees by CV, test, or training error for a given outcome |
X |
optional vector, matrix, or data.frame of predictors. If included, a 'rug' (a small vertical line for each observation) is plotted on the x-axis showing the density of |
xlab |
label of the x axis |
ylab |
label of the y axis |
return.grid |
|
... |
extra arguments are passed to plot. See |
This is the classic partial dependence plot, where the model implied effect of the chosen predictor is plotted
controlling for the other predictors. In addition to the model-implied effect, the relative influence
of the predictor is included in the x-axis label. If this is not desired, a custom label can be provided via xlab
.
Produces a plot of the model implied effect along with the relative influence of the predictor. If return.grid=TRUE
, returns the plotting matrix as well.
plot.GBMFit
, mvtb.perspec
, for other plots, mvtb.heat
to plot the covariance explained by predictors in a heatmap
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