8000 DOC: use notebook-style for plot_logistic_path.py by alexanmv · Pull Request #22536 · scikit-learn/scikit-learn · GitHub
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DOC: use notebook-style for plot_logistic_path.py #22536

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Merged
merged 3 commits into from
Feb 22, 2022
Merged

DOC: use notebook-style for plot_logistic_path.py #22536

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f2c7b43
Update plot_logistic_path.py
alexanmv Feb 18, 2022
2b008c8
Merge branch 'main' into patch-1
alexanmv Feb 19, 2022
1bcc7ab
Tweak example
lesteve Feb 22, 2022
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29 changes: 18 additions & 11 deletions examples/linear_model/plot_logistic_path.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,13 +28,11 @@
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause

from time import time
import numpy as np
import matplotlib.pyplot as plt
# %%
# Load data
# ---------

from sklearn import linear_model
from sklearn import datasets
from sklearn.svm import l1_min_c

iris = datasets.load_iris()
X = iris.data
Expand All @@ -45,14 +43,17 @@

X /= X.max() # Normalize X to speed-up convergence

# #############################################################################
# Demo path functions
# %%
# Compute regularization path
# ---------------------------

cs = l1_min_c(X, y, loss="log") * np.logspace(0, 7, 16)
import numpy as np

from sklearn import linear_model
from sklearn.svm import l1_min_c

cs = l1_min_c(X, y, loss="log") * np.logspace(0, 7, 16)

print("Computing regularization path ...")
start = time()
clf = linear_model.LogisticRegression(
penalty="l1",
solver="liblinear",
Expand All @@ -66,9 +67,15 @@
clf.set_params(C=c)
clf.fit(X, y)
coefs_.append(clf.coef_.ravel().copy())
print("This took %0.3fs" % (time() - start))

coefs_ = np.array(coefs_)

# %%
# Plot regularization path
# ------------------------

import matplotlib.pyplot as plt

plt.plot(np.log10(cs), coefs_, marker="o")
ymin, ymax = plt.ylim()
plt.xlabel("log(C)")
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