How To Install python3-imbalanced-learn on Fedora 36
In this tutorial we learn how to install python3-imbalanced-learn in Fedora 36. python3-imbalanced-learn is A Python Package to Tackle the Imbalanced Datasets in Machine Learning
Introduction
In this tutorial we learn how to install python3-imbalanced-learn on Fedora 36.
What is python3-imbalanced-learn
imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-class imbalance. It is compatible with scikit-learn and is part of scikit-learn-contrib projects.
We can use yum or dnf to install python3-imbalanced-learn on Fedora 36. In this tutorial we discuss both methods but you only need to choose one of method to install python3-imbalanced-learn.
Install python3-imbalanced-learn on Fedora 36 Using dnf
Update yum database with dnf using the following command.
sudo dnf makecache --refresh
After updating yum database, We can install python3-imbalanced-learn using dnf by running the following command:
sudo dnf -y install python3-imbalanced-learn
Install python3-imbalanced-learn on Fedora 36 Using yum
Update yum database with yum using the following command.
sudo yum makecache --refresh
After updating yum database, We can install python3-imbalanced-learn using yum by running the following command:
sudo yum -y install python3-imbalanced-learn
How To Uninstall python3-imbalanced-learn on Fedora 36
To uninstall only the python3-imbalanced-learn package we can use the following command:
sudo dnf remove python3-imbalanced-learn
python3-imbalanced-learn Package Contents on Fedora 36
/usr/lib/python3.10/site-packages/imbalanced_learn-0.9.0-py3.10.egg-info
/usr/lib/python3.10/site-packages/imbalanced_learn-0.9.0-py3.10.egg-info/PKG-INFO
/usr/lib/python3.10/site-packages/imbalanced_learn-0.9.0-py3.10.egg-info/SOURCES.txt
/usr/lib/python3.10/site-packages/imbalanced_learn-0.9.0-py3.10.egg-info/dependency_links.txt
/usr/lib/python3.10/site-packages/imbalanced_learn-0.9.0-py3.10.egg-info/not-zip-safe
/usr/lib/python3.10/site-packages/imbalanced_learn-0.9.0-py3.10.egg-info/requires.txt
/usr/lib/python3.10/site-packages/imbalanced_learn-0.9.0-py3.10.egg-info/top_level.txt
/usr/lib/python3.10/site-packages/imblearn
/usr/lib/python3.10/site-packages/imblearn/__init__.py
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/usr/share/doc/python3-imbalanced-learn
/usr/share/doc/python3-imbalanced-learn/README.rst
/usr/share/doc/python3-imbalanced-learn/examples
/usr/share/doc/python3-imbalanced-learn/examples/README.txt
/usr/share/doc/python3-imbalanced-learn/examples/api
/usr/share/doc/python3-imbalanced-learn/examples/api/README.txt
/usr/share/doc/python3-imbalanced-learn/examples/api/plot_sampling_strategy_usage.py
/usr/share/doc/python3-imbalanced-learn/examples/applications
/usr/share/doc/python3-imbalanced-learn/examples/applications/README.txt
/usr/share/doc/python3-imbalanced-learn/examples/applications/plot_impact_imbalanced_classes.py
/usr/share/doc/python3-imbalanced-learn/examples/applications/plot_multi_class_under_sampling.py
/usr/share/doc/python3-imbalanced-learn/examples/applications/plot_outlier_rejections.py
/usr/share/doc/python3-imbalanced-learn/examples/applications/plot_over_sampling_benchmark_lfw.py
/usr/share/doc/python3-imbalanced-learn/examples/applications/plot_topic_classication.py
/usr/share/doc/python3-imbalanced-learn/examples/applications/porto_seguro_keras_under_sampling.py
/usr/share/doc/python3-imbalanced-learn/examples/combine
/usr/share/doc/python3-imbalanced-learn/examples/combine/README.txt
/usr/share/doc/python3-imbalanced-learn/examples/combine/plot_comparison_combine.py
/usr/share/doc/python3-imbalanced-learn/examples/datasets
/usr/share/doc/python3-imbalanced-learn/examples/datasets/README.txt
/usr/share/doc/python3-imbalanced-learn/examples/datasets/plot_make_imbalance.py
/usr/share/doc/python3-imbalanced-learn/examples/ensemble
/usr/share/doc/python3-imbalanced-learn/examples/ensemble/README.txt
/usr/share/doc/python3-imbalanced-learn/examples/ensemble/plot_bagging_classifier.py
/usr/share/doc/python3-imbalanced-learn/examples/ensemble/plot_comparison_ensemble_classifier.py
/usr/share/doc/python3-imbalanced-learn/examples/evaluation
/usr/share/doc/python3-imbalanced-learn/examples/evaluation/README.txt
/usr/share/doc/python3-imbalanced-learn/examples/evaluation/plot_classification_report.py
/usr/share/doc/python3-imbalanced-learn/examples/evaluation/plot_metrics.py
/usr/share/doc/python3-imbalanced-learn/examples/model_selection
/usr/share/doc/python3-imbalanced-learn/examples/model_selection/README.txt
/usr/share/doc/python3-imbalanced-learn/examples/model_selection/plot_validation_curve.py
/usr/share/doc/python3-imbalanced-learn/examples/over-sampling
/usr/share/doc/python3-imbalanced-learn/examples/over-sampling/README.txt
/usr/share/doc/python3-imbalanced-learn/examples/over-sampling/plot_comparison_over_sampling.py
/usr/share/doc/python3-imbalanced-learn/examples/over-sampling/plot_illustration_generation_sample.py
/usr/share/doc/python3-imbalanced-learn/examples/over-sampling/plot_shrinkage_effect.py
/usr/share/doc/python3-imbalanced-learn/examples/pipeline
/usr/share/doc/python3-imbalanced-learn/examples/pipeline/README.txt
/usr/share/doc/python3-imbalanced-learn/examples/pipeline/plot_pipeline_classification.py
/usr/share/doc/python3-imbalanced-learn/examples/under-sampling
/usr/share/doc/python3-imbalanced-learn/examples/under-sampling/README.txt
/usr/share/doc/python3-imbalanced-learn/examples/under-sampling/plot_comparison_under_sampling.py
/usr/share/doc/python3-imbalanced-learn/examples/under-sampling/plot_illustration_nearmiss.py
/usr/share/doc/python3-imbalanced-learn/examples/under-sampling/plot_illustration_tomek_links.py
/usr/share/licenses/python3-imbalanced-learn
/usr/share/licenses/python3-imbalanced-learn/LICENSE
References
Summary
In this tutorial we learn how to install python3-imbalanced-learn on Fedora 36 using yum and [dnf]((/fedora/36/dnf/).
