How to Install and Uninstall python3-mlpy Package on Kali Linux

Last updated: September 20,2024

1. Install "python3-mlpy" package

Please follow the instructions below to install python3-mlpy on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python3-mlpy
            
                    
    
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2. Uninstall "python3-mlpy" package

In this section, we are going to explain the necessary steps to uninstall python3-mlpy on Kali Linux:


    
        
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                sudo apt remove
            
                        
                python3-mlpy
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python3-mlpy package on Kali Linux

Package: python3-mlpy
Source: mlpy
Version: 3.5.0+ds-3
Installed-Size: 199
Maintainer: Debian Science Maintainers
Architecture: all
Depends: python3-numpy, python3-scipy, python3:any, python3, python3-mlpy-lib (>= 3.5.0+ds-3)
Suggests: python3-mvpa
Size: 33436
SHA256: 70c100cfe356f572ede7f29d660fd7d9e8ccd3dbfac1364cb28bdda04984e3cd
SHA1: 36b37d29446fc4f6c5166428f4dfcdfbe06287fc
MD5sum: 45d3f95386bc51c9957dab3aaa0aee04
Description: high-performance Python package for predictive modeling
mlpy provides high level procedures that support, with few lines of
code, the design of rich Data Analysis Protocols (DAPs) for
preprocessing, clustering, predictive classification and feature
selection. Methods are available for feature weighting and ranking,
data resampling, error evaluation and experiment landscaping.
.
mlpy includes: SVM (Support Vector Machine), KNN (K Nearest
Neighbor), FDA, SRDA, PDA, DLDA (Fisher, Spectral Regression,
Penalized, Diagonal Linear Discriminant Analysis) for classification
and feature weighting, I-RELIEF, DWT and FSSun for feature weighting,
RFE (Recursive Feature Elimination) and RFS (Recursive Forward
Selection) for feature ranking, DWT, UWT, CWT (Discrete, Undecimated,
Continuous Wavelet Transform), KNN imputing, DTW (Dynamic Time
Warping), Hierarchical Clustering, k-medoids, Resampling Methods,
Metric Functions, Canberra indicators.
Description-md5:
Homepage: https://mlpy.fbk.eu/
Section: python
Priority: optional
Filename: pool/main/m/mlpy/python3-mlpy_3.5.0+ds-3_all.deb