I recently added support for sparse matrices (as defined in scipy.sparse) in some classifiers of scikits.learn. In those classes, the fit method will perform the algorithm without converting to a dense representation and will also store parameters in an efficient format. Right now, the only classese that implements ...

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I often find myself debugging python C extensions from gdb, but usually some variables are hidden because aggressive optimizations that distutils sets by default. What I did not know, is that you can prevent those optimizations by passing flags -O0 -fno-inline to gcc in keyword extra_compile_args (note: this will only ...

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One of the best things of spending summer in Paris: its parcs (here, with friends @ Parc Montsouris).

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It is now possible (using the development version as of may 2010) to use Support Vector Machines with custom kernels in scikits.learn. How to use it couldn't be more simple: you just pass a callable (the kernel) to the class constructor). For example, a linear kernel would be ...

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If your numpy installation uses system-wide BLAS libraries (this will most likely be the case unless you installed it through prebuilt windows binaries), you can retrieve this information at compile time to link python modules to BLAS. The function get_info in numpy.distutils.system_info will return a dictionary that contains ...

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Today I released a new version of the scikits.learn library for machine learning. This new release includes the new libsvm bindings, Jake VanderPlas' BallTree algorithm for *fast* nearest neighbor queries in high dimension, etc. Here is the official announcement. As usual, it can be downloaded from sourceforge or from ...

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Suppose some given data points each belong to one of two classes, and the goal is to decide which class a new data point will be in. In the case of support vector machines, a data point is viewed as a p-dimensional vector (2-dimensional in this example), and we want ...

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LibSVM is a C++ library that implements several Support Vector Machine algorithms that are commonly used in machine learning. It is a fast library that has no dependencies and most machine learning frameworks bind it in some way or another. LibSVM comes with a Python interface written in swig, but ...

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Yesterday we had an extremely productive coding sprint for the scikits.learn. The idea was to put people with common interests in a room and make them work in a single codebase. Alexandre Gramfort and Olivier Grisel worked on GLMNet, Bertrand Thirion and Gaël Varoquaux worked on univariate feature selection ...

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Today I released the first public version of Scikit-Learn (release notes). It's a python module implementing some machine learning algorithms, and it's shaping quite good. For this release I did not want to do any incompatible changes, so most of them are just bug fixes and updates. For ...

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