wildboar is a Python module for temporal machine learning and fast distance computations built on top of SciKit-Learn and Numpy distributed under the GNU General Public License Version 3.

It is currently maintained by Isak Karlsson

wildboar requires:

• Python (>= 3.4)
• NumPy (>= 1.8.2)
• SciPy (>= 0.13.3)

Some parts of wildboar is implemented using Cython. Hence, compilation requires:

• Cython (>= 0.28)

Current release: 0.3

wildboar is available through pip and can be installed with:

pip install wildboar

Universal binaries are compiled for GNU/Linux and Python 3.6 and 3.7.

If you already have a working installation of NumPy, SciPy and Cython, compiling and installing wildboar is as simple as:

python setup.py install

To install the requirements, use:

pip install -r requirements.txt

Contributions are welcome. Pull requests are encouraged to be formatted according to PEP8, e.g., using yapf.

from wildboar import ShapeletForestClassifier
c = ShapeletForestClassifier()
c.fit(x, y)

You can check the latest sources with the command:

git clone https://github.com/isakkarlsson/wildboar

If you use wildboar in a scientific publication, I would appreciate citations to the paper: Karlsson, I., Papapetrou, P. Boström, H., Generalized Random Shapelet Forests. In the Data Mining and Knowledge Discovery Journal (DAMI), 2016