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megaman is a scalable manifold learning package implemented inpython. It has a front-end API designed to be familiarto scikit-learn but harnessesthe C++ Fast Library for Approximate Nearest Neighbors (FLANN)and the Sparse Symmetric Positive Definite (SSPD) solverLocally Optimal Block Precodition Gradient (LOBPCG) methodto scale manifold learning algorithms to large data sets.It is designed for researchers and as such caches intermediarysteps and indices to allow for fast re-computation with new parameters.

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