pyoptree
Python Optimal Tree
Install
First install pyoptree through pip
pip3 install pyoptree
Then install solver (IMPORTANT!)
The user needs to have IBM Cplex or Gurobi installed on their computer, and make sure that the executable has been added to PATH environment variable (i.e. command cplex or gurobi can be run on terminal).
Example
import pandas as pd
from pyoptree.optree import OptimalHyperTreeModel, OptimalTreeModel
data = pd.DataFrame({
"index": ['A', 'C', 'D', 'E', 'F'],
"x1": [1, 2, 2, 2, 3],
"x2": [1, 2, 1, 0, 1],
"y": [1, 1, -1, -1, -1]
})
test_data = pd.DataFrame({
"index": ['A', 'B', 'C', 'D', 'E', 'F', 'G'],
"x1": [1, 1, 2, 2, 2, 3, 3],
"x2": [1, 2, 2, 1, 0, 1, 0],
"y": [1, 1, 1, -1, -1, -1, -1]
})
model = OptimalHyperTreeModel(["x1", "x2"], "y", tree_depth=2, N_min=1, alpha=0.1, solver_name="cplex")
model.train(data)
print(model.predict(test_data))Todos
- Use the solution from the previous depth tree as a "Warm Start" to speed up the time to solve the Mixed Integer Linear Programming (MILP); （Done √）
- Use the solution from sklearn's CART to give a good initial solution (Done √);
