DEnsity-BAsed CLustering
========================
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DeBaCl is a Python library for estimation of density level set trees and
nonparametric density-based clustering. Level set trees are based on the
statistically-principled definition of clusters as modes of a probability
density function. They are particularly useful for analyzing structure in
complex datasets that exhibit multi-scale clustering behavior. DeBaCl is
intended to promote the practical use of level set trees through improvements
in computational efficiency, flexible algorithms, and an emphasis on
modularity and user customizability.

The [tutorial for DeBaCl] (http://nbviewer.ipython.org/url/raw.github.com/CoAxLa
b/DeBaCl/master/docs/debacl_tutorial.ipynb) is an IPython Notebook. It is
viewable on nbviewer, or as a [PDF in the docs
folder](docs/debacl_tutorial.pdf).

The docs folder also contains a [user manual](docs/debacl_manual.pdf) with
documentation for each function and [a paper](docs/debacl_paper.pdf) describing
the statistical background of level set trees and density-based clustering.

License
-------
DeBaCl is available under the 3-clause BSD license. Please see the
[license](LICENSE.txt) for more detail.

DEnsity-BAsed CLustering
========================
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DeBaCl is a Python library for estimation of density level set trees and
nonparametric density-based clustering. Level set trees are based on the
statistically-principled definition of clusters as modes of a probability
density function. They are particularly useful for analyzing structure in
complex datasets that exhibit multi-scale clustering behavior. DeBaCl is
intended to promote the practical use of level set trees through improvements
in computational efficiency, flexible algorithms, and an emphasis on
modularity and user customizability.

The [tutorial for DeBaCl] (http://nbviewer.ipython.org/url/raw.github.com/CoAxLa
b/DeBaCl/master/docs/debacl_tutorial.ipynb) is an IPython Notebook. It is
viewable on nbviewer, or as a [PDF in the docs
folder](docs/debacl_tutorial.pdf).

The docs folder also contains a [user manual](docs/debacl_manual.pdf) with
documentation for each function and [a paper](docs/debacl_paper.pdf) describing
the statistical background of level set trees and density-based clustering.

License
-------
DeBaCl is available under the 3-clause BSD license. Please see the
[license](LICENSE.txt) for more detail.

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