mlf
Machine Learning Foundations
Offers a gentle introduction to machine learning concepts for practitioners with a statistical pedigree: decomposition of model error (bias-variance trade-off), nonlinear correlations, information theory and functional permutation/bootstrap simulations. Székely GJ, Rizzo ML, Bakirov NK. (2007). <doi:10.1214/009053607000000505>. Reshef DN, Reshef YA, Finucane HK, Grossman SR, McVean G, Turnbaugh PJ, Lander ES, Mitzenmacher M, Sabeti PC. (2011). <doi:10.1126/science.1205438>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2.1 |
rolling linux/jammy R-4.5 | mlf_1.2.1.tar.gz |
45.5 KiB |
1.2.1 |
rolling linux/noble R-4.5 | mlf_1.2.1.tar.gz |
45.4 KiB |
1.2.1 |
rolling source/ R- | mlf_1.2.1.tar.gz |
6.2 KiB |
1.2.1 |
latest linux/jammy R-4.5 | mlf_1.2.1.tar.gz |
45.5 KiB |
1.2.1 |
latest linux/noble R-4.5 | mlf_1.2.1.tar.gz |
45.4 KiB |
1.2.1 |
latest source/ R- | mlf_1.2.1.tar.gz |
6.2 KiB |
1.2.1 |
2026-04-26 source/ R- | mlf_1.2.1.tar.gz |
6.2 KiB |
1.2.1 |
2026-04-23 source/ R- | mlf_1.2.1.tar.gz |
6.2 KiB |
1.2.1 |
2026-04-09 windows/windows R-4.5 | mlf_1.2.1.zip |
48.1 KiB |
1.2.1 |
2025-04-20 source/ R- | mlf_1.2.1.tar.gz |
6.2 KiB |