Inverses and pseudoinverses. Numerical issues, speed, symmetry.

Category: benchmarking
#inv #matrix inverse #numerical analysis #numerical methods #pinv #pinvh #positive semidefinite #pseudoinverse #symmetric #benchmarking #python

The matrix inverse is a cornerstone of linear algebra, taught, along with its applications, since high school. The inverse of a matrix \$latex A\$, if it exists, is the matrix \$latex A\^{-1}\$ such that \$latex AA\^{-1} = A\^{-1}A = I_n\$. Based on the requirement that the left and …

Profiler output, benchmark standard deviation and other goodies in scikit-learn-speed

Category: scikit-learn
#gsoc #memory_profiler #scikit-learn-speed #vbench #benchmarking #python #scikit-learn

This post is about the scikit-learnbenchmarking project that I am working on, called scikit-learn-speed. This is a continuous benchmarking suite that runs and generates HTML reports using Wes McKinney’s vbench framework, to which I had to make some (useful, I hope) additions.

What it looks like now

You …