Skip to content

Latest commit

 

History

History
50 lines (43 loc) · 903 Bytes

README.md

File metadata and controls

50 lines (43 loc) · 903 Bytes

Classification and Regression Trees

Running the program

cd cart
make

Random Forest

Running the program

cd random_forest
make

Required Parameters

  • -t ../data/train_file
    • input train file to matrix
  • -s ../data/result_file
    • output predict labels to result file

Optional Parameters

  • -p 16
    • use 16 threads in a thread pool to train trees
  • -n 1000
    • use 1000 trees in the forest
  • -f 30
    • use a subset of 30 features for each tree

Gradient Boosting Regression Tree

Running the program

cd gradient_boosting
./run.sh

Required Parameters

  • train_path = "examples/train_reg.txt"
  • eval[test] = "examples/test_reg.txt"
  • test_reg = "examples/test_reg.txt"

Optional Parameters

  • booster = gbtree

  • objective = reg:linear

  • eta = 1.0

  • gamma = 1.0

  • min_child_weight = 1

  • max_depth = 3

  • num_round = 2

  • save_period = 0