from sympy.core.symbol import Symbol
import pandas
from nose.tools import assert_almost_equal
# Create some data
m = 10000
X = np.random.normal(size=(m, 10))
thresh = np.random.normal(size=10)
X_transformed = X * (X > thresh)
beta = np.random.normal(size=10)
y = np.dot(X_transformed, beta) + np.random.normal(size=m)
# Train a decision tree regressor
model = DecisionTreeRegressor()
model.fit(X, y)
print model.score(X, y)
# Inspect
def _sym_predict_decision_tree(model,
names,
current_node=0,
output_idx=0,
class_idx=0):
left = model.tree_.children_left[current_node]
right = model.tree_.children_right[current_node]
if left == -1:
assert right == -1
left_expr = RealNumber(model.tree_.value[current_node, output_idx,
class_idx])
right_expr = left_expr
