dotplot.cubist {Cubist} | R Documentation |
Lattice dotplots of the rule conditions or the linear model
coefficients produced by cubist()
objects
## S3 method for class 'cubist' dotplot(x, data = NULL, what = "splits", committee = NULL, rule = NULL, ...)
x |
a |
data |
not currently used (here for lattice compatibility) |
what |
either "splits" or "coefs" |
committee |
which committees to plot |
rule |
which rules to plot |
... |
options to pass to |
For the splits, a panel is created for each predictor. The
x-axis is the range of the predictor scaled to be between zero
and one and the y-axis has a line for each rule (within each
committee). Areas are colored as based on their region. For
example, if one rule has var1 < 10
, the linear for this rule
would be colored. If another rule had the complementary region
of var1 <= 10
, it would be on another line and shaded a
different color.
For the coefficient plot, another dotplot is made. The layout is the same except the the x-axis is in the original units and has a dot if the rule used that variable in a linear model.
a lattice::dotplot()
object
R code by Max Kuhn, original C sources by R Quinlan and modifications be Steve Weston
Quinlan. Learning with continuous classes. Proceedings of the 5th Australian Joint Conference On Artificial Intelligence (1992) pp. 343-348
Quinlan. Combining instance-based and model-based learning. Proceedings of the Tenth International Conference on Machine Learning (1993) pp. 236-243
Quinlan. C4.5: Programs For Machine Learning (1993) Morgan Kaufmann Publishers Inc. San Francisco, CA
http://rulequest.com/cubist-info.html
cubist()
, cubistControl()
,
predict.cubist()
, summary.cubist()
,
predict.cubist()
, lattice::dotplot()
library(mlbench) data(BostonHousing) ## 1 committee and no instance-based correction, so just an M5 fit: mod1 <- cubist(x = BostonHousing[, -14], y = BostonHousing$medv) dotplot(mod1, what = "splits") dotplot(mod1, what = "coefs") ## Now with 10 committees mod2 <- cubist(x = BostonHousing[, -14], y = BostonHousing$medv, committees = 10) dotplot(mod2, scales = list(y = list(cex = .25))) dotplot(mod2, what = "coefs", between = list(x = 1, y = 1), scales = list(x = list(relation = "free"), y = list(cex = .25)))