def test_drforest_smoke():
X, y = datasets.make_simulation1()
forest = DimensionReductionForestRegressor(n_estimators=100,
random_state=42,
n_jobs=-1).fit(X, y)
y_pred = forest.predict(X)
assert y_pred.shape == (1000, )
imp = forest.local_subspace_importance(np.array([[-1.5, 1.5], [0.5,
-0.5]]))
assert imp.shape == (2, 2)
import pandas as pd
from sklearn.ensemble import RandomForestRegressor
from drforest.datasets import make_simulation1
from drforest.ensemble import DimensionReductionForestRegressor
from drforest.ensemble import permutation_importance
plt.rc('font', family='serif')
fontsize = 14
n_samples = 2000
n_features = 5
X, y = make_simulation1(n_samples=n_samples,
noise=1,
n_features=n_features,
random_state=1234)
forest = DimensionReductionForestRegressor(n_estimators=500,
store_X_y=True,
n_jobs=-1,
min_samples_leaf=3,
max_features=None,
random_state=42).fit(X, y)
x0 = np.zeros(n_features)
x0[:2] = np.array([-1.5, 1.5])
local_direc_x0 = forest.local_principal_direction(x0)
local_direc_x0 *= np.sign(local_direc_x0[0])
x1 = np.zeros(n_features)