I've been working lately with Alexandre Gramfort coding the LARS
algorithm in scikits.learn. This algorithm computes the solution to
several general linear models used in machine learning: LAR, Lasso,
Elasticnet and Forward Stagewise. Unlike the implementation by
coordinate descent, the LARS algorithm gives the full coefficient path
along the …

Las week took place in Paris the second scikits.learn sprint. It was
two days of insane activity (115 commits, 6 branches, 33 coffees) in
which we did a lot of work, both implementing new algorithms and fixing
or improving old ones. This includes: * sparse version of Lasso by
coordinate …

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 …

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 …

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

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 implemented …

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 …

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 …

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 …

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 …