To Dos

HAL todo list

• Move duplicationCheck into its own function
  • Easier to test
  • Easier to try different versions
  • No real performance impact
• Alternative makeSparseMat implementations
  • C++
    • Armadillo sparseMat
    • Eigen?
    • Eventually: OpenMP and OpenACC (GPU) support
  • R
    • dplyr
    • data.table
• Alternative duplicationCheck implementations
  • C++
    • Armadillo sparseMat
    • Eigen?
• Early stopping on interactions
  • So we can avoid the super high interactions
• Interaction restarting
  • Resume adding interactions after initial partial fit to see if it improves performance
• More extensive performance profiling (RAM and CPU)
• Clear written description of all parts of the algorithm
  • Solid examples in Cheng Ju et al.’s “On Adaptive Propensity Score Truncation in Causal Inference”
• Alternative lasso implementations
  • h2o
  • C++
    • MLPACK
• Alternative prediction implementations
  • R
    • dplyr
  • C++
    • Armadillo / MLPACK
• Larger algorithm re-implementation
  • Saving the indicator functions in a list with two vectors: variables used (e.g. x1, x3), and cutoffs (1.5, 10.2)
• Wider R ML framework support
  • mlr wrapper
  • caret wrapper
• Python implementation based on C++ core (ala xgboost, arborist, etc.)
  • then scikit-learn wrapper