Description Usage Arguments Value Author(s) References See Also Examples
View source: R/BoostVimp.plot.R
Dot chart of variable and/or interaction importance for the variables/interactions with the largest magnitude variable importance scores.
1 | BoostVimp.plot(fit, num=10, pred, norm=TRUE, titles=TRUE)
|
fit |
an object of class LBoost. |
num |
number of variables/interactions to be included on plot. |
pred |
logical. If TRUE, a variable importance plot is constructed for individual variables. |
norm |
logical. If TRUE, variable/interaction importance scores are normalized such that the largest importance score takes value one and all other values are scaled accordingly. |
titles |
logical. If FALSE, titles are not included on the plot. |
Plots up to three separate plots of the predictors/interactions with the largest magnitude variable importance score. If pred
=TRUE is specified, one plot will be of the largest magnitude individual variable importance scores. Note, pred.imp
must also have been specified as TRUE when running LBoost
to be able to generate this plot. A plot for each type of interaction importance measure will also be generated if PI.imp
="Both" when running LBoost
. If only "Permutation" or "AddRemove" was specified for PI.imp
, one plot will be generated for the interaction importance type specified in LBoost
.
Bethany Wolf wolfb@musc.edu
Wolf, B.J., Slate, E.H., Hill, E.G. (2010) Logic Forest: An ensemble classifier for discovering logical combinations of binary markers. Bioinformatics.
persistence.plot
, submatch.plot
1 2 3 4 5 | data(LBoost.fit)
#Plot of top 10 predictors based on variable importance from the LBoost
#model LBoost.fit
BoostVimp.plot(fit=LBoost.fit, num=10, pred=TRUE, norm=TRUE, titles=TRUE)
|
Loading required package: LogicReg
Loading required package: survival
Loading required package: CircStats
Loading required package: MASS
Loading required package: boot
Attaching package: 'boot'
The following object is masked from 'package:survival':
aml
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