I decided to test my new Locally Linear Embedding (LLE)
implementation against a real dataset. At first I didn't think this
would turn out very well, since LLE seems to be somewhat fragile,
yielding largely different results for small differences in parameters
such as number of neighbors or tolerance, but …

I've been working lately in improving the low-level API of the libsvm
bindings in scikit-learn. The goal is to provide an API that encourages
an efficient use of these libraries for expert users. These are methods
that have lower overhead than the object-oriented interface as they
are closer to the …

Today got merged some changes I made to function
scipy.linalg.get_blas_funcs(). The main enhacement is that
get_blas_funcs() now also accepts a single string as input parameter
and a dtype, so that fetching the BLAS function for a specific type
becomes more natural. For example, fetching the gemm routine for …

I've been working for some time on implementing a locally linear
embedding algorithm for the upcoming manifold module in scikit-learn.
While several implementations of this algorithm exist in Python, as far
as I know none of them is able to use a sparse eigensolver in the last
step of the …

The guys behind pythonxy have been kind enough to add the latest
scikit-learn as an additional plugin for their distribution. Having
scikit-learn being in both pythonxy and EPD will hopefully make it
easier to use for Windows users. For now I will continue
to make windows precompiled binaries, but pythonxy …

The following algorithm computes the Least squares solution || Ax -
b|| subject to the equality constrain Bx = d. It's a classic algorithm
that can be implemented only using a QR decomposition and a least
squares solver. This implementation uses numpy and scipy. It makes use
of the new linalg.solve_triangular function …

Profiling Python extensions has not been a pleasant experience for me,
so I made my own package to do the job. Existing alternatives were
either hard to use, forcing you to recompile with custom flags like
gprofile or desperately slow like valgrind/callgrind. The package I'll
talk about is called …

Yesterday was the scikit-learn coding sprint in Paris. It was great to
meet with old developers (Vincent Michel) and new ones: some of whom I
was already familiar with from the mailing list while others came just
to say hi and get familiar with the code. It was really great …

One thing I'd really like to see done in this Friday's scikit-learn
sprint is to have full support for Python 3. There's a branch were
the hard word has been done (porting C extensions, automatic 2to3
conversion, etc.), although joblib still has some bugs and no one has
attempted to …

**Update: a fast and stable norm was added to scipy.linalg in August
2011 and will be available in scipy 0.10** Last week I discussed with
Gael how we should compute the euclidean norm of a vector a using
SciPy. Two approaches suggest themselves, either calling
scipy.linalg.norm …