Skip to content

Latest commit

 

History

History
15 lines (12 loc) · 898 Bytes

README.md

File metadata and controls

15 lines (12 loc) · 898 Bytes

Cost-Complexity pruning of Random Forests ISMM 2017

  • Paper, Poster,
  • Only Classification tasks have been evaluated. Overview

Datasets

  • Download winequality dataset, and other datasets and change utils.py to add new datasets to test out the pruning algorithm.

Todo

  • Calculate the test leaves id at the same time as train leaves id
    • Then predict with optimal leaf labeling

New references

  • Impact of subsampling and pruning on random forests Paper
  • Understanding variable importances in forests of randomized trees Paper