jolars / benchmark_mcp

Benchmark repository for MCP

BenchOpt is a package to simplify and make more transparent and reproducible the comparisons of optimization algorithms. Regression with the Minimax Concave Penalty (MCP) consists in solving the following program:

with the penalty

where n (or n_samples) stands for the number of samples, p (or n_features) stands for the number of features and

y ∈ ℝⁿ, X = [x₁^⊤, …, x_n^⊤]^⊤ ∈ ℝ^n × p

Install

This benchmark can be run using the following commands:

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

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_mcp -s cd -d simulated --max-runs 10 --n-repetitions 5

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