From ff36b7828a7fa53cfc8178c8379d54575a743d94 Mon Sep 17 00:00:00 2001 From: Rafael Menelau Date: Thu, 11 Apr 2024 21:12:01 -0400 Subject: [PATCH 1/2] version 0.3.7 --- deslib/__init__.py | 2 +- setup.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/deslib/__init__.py b/deslib/__init__.py index 3d62b687..8d75c301 100644 --- a/deslib/__init__.py +++ b/deslib/__init__.py @@ -23,4 +23,4 @@ # list of all modules available in the library __all__ = ['des', 'dcs', 'static', 'util', 'tests'] -__version__ = '0.4.dev' +__version__ = '0.3.7' diff --git a/setup.py b/setup.py index 0cc1f10b..59dfdd47 100644 --- a/setup.py +++ b/setup.py @@ -11,7 +11,7 @@ README = f.read() setup(name='DESlib', - version='0.4.dev', + version='0.3.7', url='https://github.com/Menelau/DESlib', maintainer='Rafael M. O. Cruz, L. G. Hafemann', maintainer_email='rafaelmenelau@gmail.com', From 554b0231f65ea9bd978dd92d3bc59d21decd4fff Mon Sep 17 00:00:00 2001 From: Rafael Menelau Date: Thu, 11 Apr 2024 23:29:23 -0400 Subject: [PATCH 2/2] updating examples according to the new sklearn version --- examples/example_calibrating_classifiers.py | 2 +- examples/plot_random_forest.py | 5 +++-- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/examples/example_calibrating_classifiers.py b/examples/example_calibrating_classifiers.py index 7c115ff4..54daceca 100644 --- a/examples/example_calibrating_classifiers.py +++ b/examples/example_calibrating_classifiers.py @@ -93,7 +93,7 @@ # DS methods. calibrated_pool = [] for clf in pool_classifiers: - calibrated = CalibratedClassifierCV(base_estimator=clf, cv='prefit') + calibrated = CalibratedClassifierCV(estimator=clf, cv='prefit') calibrated.fit(X_dsel, y_dsel) calibrated_pool.append(calibrated) diff --git a/examples/plot_random_forest.py b/examples/plot_random_forest.py index fdd4caa7..7cc35fbb 100644 --- a/examples/plot_random_forest.py +++ b/examples/plot_random_forest.py @@ -43,7 +43,8 @@ rng = np.random.RandomState(42) # Fetch a classification dataset from OpenML -data = fetch_openml(name='credit-g', version=1, cache=False, as_frame=False) +data = fetch_openml(name='phoneme', version=1, + cache=False, as_frame=False) X = data.data y = data.target # split the data into training and test data @@ -57,7 +58,7 @@ RF.fit(X_train, y_train) X_train, X_dsel, y_train, y_dsel = train_test_split(X_train, y_train, - test_size=0.50, + test_size=0.750, random_state=rng) stacked = StackedClassifier(RF, LogisticRegression()) pFad - Phonifier reborn

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