A little experiment to see what low rank approximation looks like. These are the best rank-k approximations (in the Frobenius norm) to the a natural image for increasing values of k and an original image of rank 512. Python code can be found here. GIF...
In scipy's development version there's a new function closely related to the QR-decomposition of a matrix and to the least-squares solution of a linear system. What this function does is to compute the QR-decomposition of a matrix and then multiply the...
Last week we released a new version of scikit-learn. The Changelog is particularly impressive, yet personally this release is important for other reasons. This will probably be my last release as a paid engineer. I'm starting a PhD next month, and alth...
I've been working lately in improving the scikit-learn example gallery to show also a small thumbnail of the plotted result. Here is what the gallery looks like now: And the real thing should be already displayed in the development-documentation. The ...
Today's coding sprint was a bit more crowded, with some notable scipy hackers such as Ralph Gommers, Stefan van der Walt, David Cournapeau or Fernando Perez from Ipython joining in. On what got done: - We merged Jake's new BallTree code. This is a pur...
As a warm-up for the upcoming EuroScipy-conference, some of the scikit-learn developers decided to gather and work together for a couple of days. Today was the first day and there was only a handfull of us, as the real kickoff is expected tomorrow. Som...
Ridge coefficients for multiple values of the regularization parameter can be elegantly computed by updating the thin SVD decomposition of the design matrix: import numpy as np from scipy import linalg def ridge(A, b, alphas): """ ...
I haven't worked in the manifold module since last time, yet thanks to Jake VanderPlas there are some cool features I can talk about. First of, the ARPACK backend is finally working and gives factor one speedup over the lobcpg + PyAMG approach. The key...
The manifold module in scikit-learn is slowly progressing: the locally linear embedding implementation was finally merged along with some documentation. At about the same time but in a different timezone, Jake VanderPlas began coding other manifold lea...
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 pa...
