Description Usage Format Source References Examples
The l1 clustering algorithm from the clusterpath package was applied to the iris dataset and the breakpoints in the solution path are stored in this data frame.
1 |
A data frame with 9643 observations on the following 8 variables.
row
a numeric vector: row of the original iris data matrix
Species
a factor with levels setosa
versicolor
virginica
: Species from corresponding row
alpha
a numeric vector: the value of the optimal solution.
lambda
a numeric vector: the regularization parameter (ie point in the path).
col
a factor with levels Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
: column
from the original iris data.
gamma
a factor with levels 0
: parameter from clustering.
norm
a factor with levels 1
parameter from clustering.
solver
a factor with levels path
algorithm used for
clustering.
clusterpath package
clusterpath article
1 2 3 4 5 6 7 8 | data(iris.l1.cluster,package="directlabels")
iris.l1.cluster$y <- iris.l1.cluster$alpha
library(ggplot2)
p <- ggplot(iris.l1.cluster,aes(lambda,y,group=row,colour=Species))+
geom_line(alpha=1/4)+
facet_grid(col~.)
p2 <- p+xlim(-0.0025,max(iris.l1.cluster$lambda))
print(direct.label(p2,list(first.points,get.means)))
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