Note
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Pixel importances with a parallel forest of treesΒΆ
This example shows the use of forests of trees to evaluate the importance of the pixels in an image classification task (faces). The hotter the pixel, the more important.
The code below also illustrates how the construction and the computation of the predictions can be parallelized within multiple jobs.
Traceback (most recent call last):
File "/build/scikit-learn-0.20.0+dfsg/examples/ensemble/plot_forest_importances_faces.py", line 25, in <module>
data = fetch_olivetti_faces()
File "/build/scikit-learn-0.20.0+dfsg/.pybuild/cpython3_3.6/build/sklearn/datasets/olivetti_faces.py", line 91, in fetch_olivetti_faces
data_home = get_data_home(data_home=data_home)
File "/build/scikit-learn-0.20.0+dfsg/.pybuild/cpython3_3.6/build/sklearn/datasets/base.py", line 56, in get_data_home
makedirs(data_home)
File "/usr/lib/python3.6/os.py", line 210, in makedirs
makedirs(head, mode, exist_ok)
File "/usr/lib/python3.6/os.py", line 220, in makedirs
mkdir(name, mode)
PermissionError: [Errno 13] Permission denied: '/nonexistent'
print(__doc__)
from time import time
import matplotlib.pyplot as plt
from sklearn.datasets import fetch_olivetti_faces
from sklearn.ensemble import ExtraTreesClassifier
# Number of cores to use to perform parallel fitting of the forest model
n_jobs = 1
# Load the faces dataset
data = fetch_olivetti_faces()
X = data.images.reshape((len(data.images), -1))
y = data.target
mask = y < 5 # Limit to 5 classes
X = X[mask]
y = y[mask]
# Build a forest and compute the pixel importances
print("Fitting ExtraTreesClassifier on faces data with %d cores..." % n_jobs)
t0 = time()
forest = ExtraTreesClassifier(n_estimators=1000,
max_features=128,
n_jobs=n_jobs,
random_state=0)
forest.fit(X, y)
print("done in %0.3fs" % (time() - t0))
importances = forest.feature_importances_
importances = importances.reshape(data.images[0].shape)
# Plot pixel importances
plt.matshow(importances, cmap=plt.cm.hot)
plt.title("Pixel importances with forests of trees")
plt.show()
Total running time of the script: ( 0 minutes 0.000 seconds)