# First thoughts on Orthogonal Matching Pursuit

I am working on implementing the Orthogonal Matching Pursuit (OMP) algorithm for the scikit. It is an elegant algorithm (that almost writes itself in Numpy!) to compute a greedy approximation to the solution of a sparse coding problem:

\$\$ \text{argmin} \big|\big|\gamma\big|\big|_0 \text{ subject to }\big …

# Sparse PCA

I have been working on the integration into the scikits.learn codebase of a sparse principal components analysis (SparsePCA) algorithm coded by Gaël and Alexandre and based on [[1]][]. Because the name “sparse PCA” has some inherent ambiguity, I will describe in greater depth what problem we are actually solving …

# Customizing scikits.learn for a specific text analysis task

Category: scikit-learn
#nlp #scikit-learn

Scikits.learn is a great general library, but machine learning has so many different application, that it is often very helpful to be able to extend its API to better integrate with your code. With scikits.learn, this is extremely easy to do using inheritance and using the pipeline module …