BINF301 Machine Learning for Systems Biology
  1. Regularized regression
  2. Implementation
  • Home
  • Introduction to Julia
  • Cluster analysis
    • Path-breaking paper
    • Theory
    • Implementation
  • Statistical significance
    • Path-breaking paper
    • Theory
    • Implementation
  • Regularized regression
    • Path-breaking paper
    • Theory
    • Implementation
  • Dimensionality reduction
    • Path-breaking paper
    • Theory (PCA)
    • Theory (t-SNE, UMAP)
    • Implementation
  • Causal inference
    • Path-breaking paper
    • Theory
    • Implementation
  • Bayesian networks
    • Path-breaking paper
    • Theory
  • Gaussian processes
    • Path-breaking paper
    • Theory
    • Implementation
  • Neural networks
    • Path-breaking paper
    • Theory
  • Appendix
  1. Regularized regression
  2. Implementation

Regularized regression notebook

Two Pluto notebooks “Regularized_regression_Glmnet.jl” and “Regularized_regression_MLJ.jl” are available:

  • On JuliaHub, here and here
  • In the BINF301-code repository

Make sure you have followed the software installation instructions in the Introduction to Julia page!

Theory
Path-breaking paper