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ENH test isotonic calibration on simulation data & FIX correct joblib dependency error #4

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ENH test isotonic calibration on simulation data & FIX correct joblib dependency error #4

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14 changes: 14 additions & 0 deletions examples/overlapping_gaussians.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@

color_dict = {
"HonestRF": "#F41711",
"Iso-HonestRF": "#ce406b",
"RF": "#1b9e77",
"SigRF": "#377eb8",
"IRF": "#fdae61",
Expand All @@ -40,6 +41,18 @@
n_jobs=n_jobs,
),
),
(
"Iso-HonestRF",
CalibratedClassifierCV(
base_estimator=HonestForestClassifier(
n_estimators=n_estimators // clf_cv,
max_features=max_features,
n_jobs=n_jobs,
),
method="isotonic",
cv=clf_cv,
),
),
Comment on lines +44 to +55
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I would say don't change this file? Leave the honest + IRF for just the notebook. This way the main figure in the repo reflects the paper and isn't as confusing to first time viewers.

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Okay, will revert the changes.

(
"IRF",
CalibratedClassifierCV(
Expand Down Expand Up @@ -168,3 +181,4 @@ def likelihood(X):
# ax.set_title("Posterior probabilities")
plt.tight_layout()
plt.savefig("./figures/overlapping_gaussians.png")

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