Description Details References

This package provides access to five of the most popular clustering algorithms in the subspace paradigm.

The algorithms `CLIQUE`

, `P3C`

, `ProClus`

,
`SubClu`

and `FIRES`

can be applied to data.frames and matrices and will
return S3 objects representing clusterings. For example, using the built-in
demo dataset, you can do:

`>data("subspace_dataset")`

```
>clustering <-
P3C(subspace_dataset,PoissonThreshold=2)
```

`>clustering`

```
Subspace clustering generated by the package Subspace, containing 12
clusters.
```

These *subspace_clustering* objects are actually just lists of
*subspace_cluster* objects, which can be accessed as follows.

`>clustering[[1]]`

```
Subspace cluster generated by the package
Subspace. This cluster consists of 140 objects in a 3 dimensional subspace.
```

Each of these clusters then holds a vector representing its subspace and a
vector with the indexes of the objects the belong in this cluster. In this
example, these could be accessed as `clustering[[1]]$objects`

and
`clustering[[1]]$subspace`

.

This package also provides a `plot`

method for
*subspace_clustering* objects:

`>plot(clustering,subspace_dataset)`

```
Showing dynamic
visualisation. Press Escape/Ctrl + C to stop.
```

These plots are created using the `ggvis`

package.

Finally, you can save clusterings to a file using the
`clustering_from_file`

and `clustering_to_file`

functions.

For example you could save the clustering from this example to a file and load the true clustering of the demo dataset:

`>clustering_to_file(clustering,file_path="clustering.txt")`

`>path_to_clustering <- paste(path.package("subspace"),"/extdata/subspace_dataset.true",sep="")`

`true_clustering <- clustering_from_file(file_path=path_to_clustering)`

M<c3><bc>ller E., G<c3><bc>nnemann S., Assent I., Seidl T.: Evaluating Clustering in Subspace Projections of High Dimensional Data http://dme.rwth-aachen.de/OpenSubspace/ In Proc. 35th International Conference on Very Large Data Bases (VLDB 2009), Lyon, France. (2009)

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