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SPArse Modeling Sofware
The spams package implements several convex optimization problem solvers that are useful for machine learning. However it is difficult to install, and could use improved documentation.
The glmnet package implements solvers for some of the same problems (LASSO, L1-regularized logistic regression) but not others (e.g. trace-norm regularization).
- Get the spams package on github so that it installs with
devtools::install_github. - Improve documentation and write some vignettes.
The R community will for the first time be able to solve a variety of sparse machine learning problems.
Please contact Pierre Neuvial and Julien Chiquet after solving at least one of the tests below.
Several tests that potential students can do to demonstrate their capabilities for this particular project. Please modify the suggestions below to make them specific for your project.
- Easy: something that any useR should be able to do, e.g. download some existing package listed in the Related Work, and run it on some example data.
- Medium: something a bit more complicated. You can encourage students to write a script or some functions that show their R coding abilities.
- Hard: Can the student write a package with Rd files, tests, and vigettes? If your package interfaces with non-R code, can the student write in that other language?
Students, please post a link to your test results here.