Benchopt Benchmark for Linear ICA

Benchopt is a package to simplify and make more transparent and reproducible the comparisons of optimization algorithms. This benchmark is dedicated to Independent Component Analysis (ICA):

$$X = A S$$

where

$$X \in \mathbb{R}^{p \times n}, A \in \mathbb{R}^{p \times p} \text{ and } S \in \mathbb{R}^{p \times n}$$

such that $n$ (or n_samples) stands for the number of samples, $p$ (or n_features) stands for the number of features. The purpose of linear ICA is to recover the mixing matrix $A$ from $X$.

where X is n_features x n_samples, A is n_features x n_features and S is n_features x n_samples. The purpose of ICA is to recover the mixing matrix A from X.

Install

This benchmark can be run using the following commands:

$ pip install -U benchopt
$ git clone https://github.com/benchopt/benchmark_linear_ica
$ benchopt run benchmark_linear_ica

Apart from the problem, options can be passed to benchopt run, to restrict the benchmarks to some solvers or datasets, e.g.:

$ benchopt run benchmark_linear_ica -s fastica -d simulated --max-runs 10 --n-repetitions 10

Use benchopt run -h for more details about these options, or visit https://benchopt.github.io/api.html.