How to Install and Uninstall python3-sklearn-genetic-opt.noarch Package on Fedora 38
Last updated: March 01,2025
1. Install "python3-sklearn-genetic-opt.noarch" package
This guide covers the steps necessary to install python3-sklearn-genetic-opt.noarch on Fedora 38
$
sudo dnf update
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$
sudo dnf install
python3-sklearn-genetic-opt.noarch
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2. Uninstall "python3-sklearn-genetic-opt.noarch" package
This tutorial shows how to uninstall python3-sklearn-genetic-opt.noarch on Fedora 38:
$
sudo dnf remove
python3-sklearn-genetic-opt.noarch
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$
sudo dnf autoremove
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3. Information about the python3-sklearn-genetic-opt.noarch package on Fedora 38
Last metadata expiration check: 2:29:27 ago on Sat Mar 16 22:59:57 2024.
Available Packages
Name : python3-sklearn-genetic-opt
Version : 0.9.0
Release : 4.fc38
Architecture : noarch
Size : 84 k
Source : python-sklearn-genetic-opt-0.9.0-4.fc38.src.rpm
Repository : fedora
Summary : Hyperparameters tuning and feature selection
URL : https://github.com/rodrigo-arenas/Sklearn-genetic-opt
License : MIT
Description : scikit-learn models hyperparameters tuning and feature selection, using
: evolutionary algorithms. This is meant to be an alternative to popular
: methods inside scikit-learn such as Grid Search and Randomized Grid
: Search for hyperparameteres tuning, and from RFE, Select From Model for
: feature selection. Sklearn-genetic-opt uses evolutionary algorithms
: from the DEAP package to choose the set of hyperparameters that
: optimizes (max or min) the cross-validation scores, it can be used
: for both regression and classification problems.
Available Packages
Name : python3-sklearn-genetic-opt
Version : 0.9.0
Release : 4.fc38
Architecture : noarch
Size : 84 k
Source : python-sklearn-genetic-opt-0.9.0-4.fc38.src.rpm
Repository : fedora
Summary : Hyperparameters tuning and feature selection
URL : https://github.com/rodrigo-arenas/Sklearn-genetic-opt
License : MIT
Description : scikit-learn models hyperparameters tuning and feature selection, using
: evolutionary algorithms. This is meant to be an alternative to popular
: methods inside scikit-learn such as Grid Search and Randomized Grid
: Search for hyperparameteres tuning, and from RFE, Select From Model for
: feature selection. Sklearn-genetic-opt uses evolutionary algorithms
: from the DEAP package to choose the set of hyperparameters that
: optimizes (max or min) the cross-validation scores, it can be used
: for both regression and classification problems.