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L1 Trend Filtering

This is a Python package wrapper around the C solver for the l1 trend filtering algorithm written by Kwangmoo Koh, Seung-Jean Kim and Stephen Boyd. It is compatible with scikit-learn_.

Documentation / Website: https://joshloyal.github.io/l1tf

Example

Example that shows how to learn a one dimensional subspace from a dataset with ten features:

.. code-block:: python

print("Hello, world!")

Installation

Dependencies

L1 Trend Filtering requires:

• Python (>= 2.7 or >= 3.4)
• NumPy (>= 1.8.2)
• SciPy (>= 0.13.3)
• Scikit-learn (>=0.17)

Additionally, to run examples, you need matplotlib(>=2.0.0).

Installation

You need a working installation of numpy and scipy to install L1 Trend Filtering. If you have a working installation of numpy and scipy, the easiest way to install l1tf is using pip::

pip install -U l1tf

If you prefer, you can clone the repository and run the setup.py file. Use the following commands to get the copy from GitHub and install all the dependencies::

git clone https://github.com/joshloyal/l1tf.git
cd l1tf
pip install .

Or install using pip and GitHub::

pip install -U git+https://github.com/joshloyal/l1tf.git

Testing

After installation, you can use pytest to run the test suite via setup.py::

python setup.py test

References: