How to Install and Uninstall python3-niaaml.noarch Package on Fedora 39

Last updated: January 16,2025

1. Install "python3-niaaml.noarch" package

Here is a brief guide to show you how to install python3-niaaml.noarch on Fedora 39


    
        
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                sudo dnf update
            
                    
    
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            $
        

        
            
                sudo dnf install
            
                        
                python3-niaaml.noarch
            
                    
    
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2. Uninstall "python3-niaaml.noarch" package

Please follow the guidance below to uninstall python3-niaaml.noarch on Fedora 39:


    
        
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                sudo dnf remove
            
                        
                python3-niaaml.noarch
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the python3-niaaml.noarch package on Fedora 39

Last metadata expiration check: 4:55:05 ago on Thu Mar 7 11:44:58 2024.
Available Packages
Name : python3-niaaml
Version : 1.1.12
Release : 3.fc39
Architecture : noarch
Size : 131 k
Source : python-niaaml-1.1.12-3.fc39.src.rpm
Repository : fedora
Summary : Python automated machine learning framework
URL : https://github.com/lukapecnik/NiaAML
License : MIT
Description : NiaAML is a framework for Automated Machine Learning based on nature-inspired
: algorithms for optimization. The framework is written fully in Python. The
: name NiaAML comes from the Automated Machine Learning method of the same name.
: Its goal is to compose the best possible classification pipeline for the given
: task efficiently using components on the input. The components are divided
: into three groups: feature selection algorithms, feature transformation
: algorithms and classifiers. The framework uses nature-inspired algorithms
: for optimization to choose the best set of components for the
: classification pipeline, and optimize their hyperparameters.