Description Usage Arguments Examples
Produces a table containing the most important Rules or linear terms
1 | importance_hs(model, k = 10)
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model |
list containing a model of class "HorseRuleFit". |
k |
number of most important rules to be shown in the table. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | library(MASS)
library(horserule)
data(Boston)
# Split in train and test data
N = nrow(Boston)
train = sample(1:N, 400)
Xtrain = Boston[train,-14]
ytrain = Boston[train, 14]
Xtest = Boston[-train, -14]
ytest = Boston[-train, 14]
hrres = HorseRuleFit(X = Xtrain, y=ytrain,
thin=1, niter=100, burnin=10,
L=5, S=6, ensemble = "both", mix=0.3, ntree=100,
intercept=FALSE, linterms=1:13, ytransform = "log",
alpha=1, beta=2, linp = 1, restricted = 0)
#Create an importance table containing the 10 most important rules and linear terms
importance_hs(hrres, k=10)
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