R: Clustering of the iris data with the l1 clusterpath

iris.l1.cluster {directlabels} | R Documentation

## Clustering of the iris data with the l1 clusterpath

### Description

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.

### Usage

    data(iris.l1.cluster)

### Format

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.

### Source

clusterpath package

### References

clusterpath article

### Examples

    data(iris.l1.cluster,package="directlabels")
    iris.l1.cluster$y <- iris.l1.cluster$alpha
    if(require(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)))
    }

[Package directlabels version 2018.05.22 Index]