LogicForest (version 2.1.0)

vimp.plot: Variable and Interaction Importance Plots for a Logic Forest Model

Description

Dot chart of variable and/or interaction importance for the variables/interactions with the largest magnitude variable importance scores.

Usage

vimp.plot(fit, num=10, type=2, norm=TRUE, titles=TRUE)

Arguments

fit
an object of class logforest.
num
number of variables/interactions to be included on plot.
type
type of plot to be constructed: type=0 generates a plot of the individual variables with the largest importance score, type=1 generated a plot of the interaction terms with the largest importance score, and type=2 generates side by side plot of the most important single variable and the most important interactions from a logic forest model.
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.

Value

References

Wolf, B.J., Slate, E.H., Hill, E.G. (2010) Logic Forest: An ensemble classifier for discovering logical combinations of binary markers. Bioinformatics.

See Also

persistence.plot, submatch.plot

Examples

Run this code
data(logforest.fit)

#Plot of top 10 predictors based on variable importance from logforest
vimp.plot(fit=logforest.fit, type=0, norm=FALSE)

#Plot of top 10 interactions based on variable importance from 
vimp.plot(fit=logforest.fit, num=10, type=1, norm=FALSE)

#Plots of top 10 predictors and interactions based on variable
#importance from logforest
vimp.plot(fit=logforest.fit, num=10, type=2, norm=FALSE)

#Plots of top 10 predictors and interactions based on normalized
#variable importance from logforest
vimp.plot(fit=logforest.fit, num=10, type=2)

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