Fabian’s blog

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 as follows:

import numpy as np
def my_kernel(x, y):
  […]

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 to know whether we can […]

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 this interface is inherently slow […]

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 and Vincent worked on Bayesian Regression.

I […]

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 the next release, however, some more radical changes […]

This week we created a sourceforge project to host our development of scikit-learn. Although the project already had a directory in scipy’s repo, we needed more flexibility in the user management and in the mailing list creation, so we opted for SourceForge.
To be honest, after using git and Google Code for bug tracking, I was […]