Python package providing scikit-learn compatible classifier based on Reflective Random Indexing (RRI) [1].
Documentation
The documentation is hosted on http://sklearn-rri.readthedocs.io/
Installation
Latest from the source:
git clone https://github.com/cmick/sklearn-rri.git cd sklearn-rri python setup.py install
Using PyPI:
pip install sklearn-rri
Dependencies
sklearn-rri requires:
NumPy (>= 1.11.0)
SciPy (>= 0.16.0)
scikit-learn (>= 0.17.0)
Examples
>>> from sklearn_rri import ReflectiveRandomIndexing
>>> from sklearn.random_projection import sparse_random_matrix
>>> X = sparse_random_matrix(100, 100, density=0.01, random_state=42)
>>> rri = ReflectiveRandomIndexing(50, random_state=42)
>>> rri.fit(X)
ReflectiveRandomIndexing(n_components=50, n_iter=3, norm=True,
random_state=42, seed='auto')
>>> rri.transform(X)
<100x50 sparse matrix of type '<class 'numpy.float64'>'
with 1154 stored elements in Compressed Sparse Row format>References
[1] Trevor Cohen, Roger Schaneveldt, and Dominic Widdows,, Reflective Random Indexing and Indirect Inference: A Scalable Method for Discovery of Implicit Connections, 2010. https://www.ncbi.nlm.nih.gov/pubmed/19761870
1 maintainer
Metadata
1 maintainer
Release files for sklearn-rri 0.1.0
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