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scikit-learn compatible classifier based on RRI

Project description

Python package providing scikit-learn compatible classifier based on Reflective Random Indexing (RRI) [1].


The documentation is hosted on


Latest from the source:

git clone
cd sklearn-rri
python install

Using PyPI:

pip install sklearn-rri


sklearn-rri requires:

  • NumPy (>= 1.11.0)
  • SciPy (>= 0.16.0)
  • scikit-learn (>= 0.17.0)


>>> 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)
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>


[1] Trevor Cohen, Roger Schaneveldt, and Dominic Widdows,, Reflective Random Indexing and Indirect Inference: A Scalable Method for Discovery of Implicit Connections, 2010.

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