How to Install and Uninstall umap-learn Package on Kali Linux

Last updated: September 28,2024

Deprecated! Installation of this package may no longer be supported.

1. Install "umap-learn" package

In this section, we are going to explain the necessary steps to install umap-learn on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                umap-learn
            
                    
    
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2. Uninstall "umap-learn" package

This guide let you learn how to uninstall umap-learn on Kali Linux:


    
        
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                sudo apt remove
            
                        
                umap-learn
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the umap-learn package on Kali Linux

Package: umap-learn
Version: 0.4.5+dfsg-3
Installed-Size: 339
Maintainer: Debian Med Packaging Team
Architecture: all
Depends: python3-numba, python3-numpy, python3-scipy, python3-sklearn, python3:any
Size: 55448
SHA256: bfe8a31625aa503b5ee8f142e3e3c942196ac597043f62a78fc036a623312761
SHA1: 86664df1bf47c339da584020e9ef222d0e31374d
MD5sum: af7210f4c9cd4f1e998262a21368dc95
Description: Uniform Manifold Approximation and Projection
Uniform Manifold Approximation and Projection (UMAP) is a dimension
reduction technique that can be used for visualisation similarly to t-
SNE, but also for general non-linear dimension reduction. The algorithm
is founded on three assumptions about the data:
.
1. The data is uniformly distributed on a Riemannian manifold;
2. The Riemannian metric is locally constant (or can be
approximated as such);
3. The manifold is locally connected.
.
From these assumptions it is possible to model the manifold with a fuzzy
topological structure. The embedding is found by searching for a low
dimensional projection of the data that has the closest possible
equivalent fuzzy topological structure.
Description-md5: 949d5d3304fc30065a0bd753c8886c71
Homepage: https://github.com/lmcinnes/umap
Section: science
Priority: optional
Filename: pool/main/u/umap-learn/umap-learn_0.4.5+dfsg-3_all.deb