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    A new version of nnetsauce (randomized and quasi-randomized ‘neural’ networks)

    T. Moudiki发表于 2023-04-02 00:00:00
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    [This article was first published on T. Moudiki's Webpage - R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
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    Content:

    • nnetsauce’s new version
    • Installing nnetsauce for Python
    • About nnetsauce for R

    nnetsauce’s new version

    A new version of nnetsauce, v0.12.0, is available on PyPI and for conda. It’s been mostly tested on Linux and macOS platforms. For Windows users: you can use the Windows Subsystem for Linux in case it doesn’t work directly on your computer.

    As a reminder, nnetsauce does Statistical/Machine Learning (regression, classification, and time series forecasting for now) using randomized and quasi-randomized neural networks layers. More precisely, every model in nnetsauce is based on components g(XW + b), where:

    • X is a matrix containing explanatory variables and optional clustering information. Clustering the inputs helps in taking into account data’s heterogeneity before model fitting.
    • W creates new, additional explanatory variables from X. W can be drawn from various random and quasi-random sequences.
    • b is an optional bias parameter.
    • g is an activation function such as ReLU or the hyperbolic tangent, that makes the combination of explanatory variables – through W – nonlinear.

    Examples of use of nnetsauce are available on GitHub, here (including R Markdown examples) and here.

    RVFL

    v0.12.0 is an important release, because it’s totally written in Python (using numpy, scipy, jax, and scikit-learn), and doesn’t use C++ nor Cython anymore. Because of this, nnetsauce is faster to install, and easier to maintain.

    If you like using nnetsauce, do not hesitate to star the repo or submit a pull request!

    Installing nnetsauce for Python

    • 1st method: by using pip at the command line for the stable version
    pip install nnetsauce
    
    • 2nd method: using conda (Linux and macOS only for now)
    conda install -c conda-forge nnetsauce 
    
    • 3rd method: from Github, for the development version
    pip install git+https://github.com/Techtonique/nnetsauce.git
    

    or in a virtual environment:

    git clone https://github.com/Techtonique/nnetsauce.git
    cd nnetsauce
    make install
    

    About nnetsauce for R

    The R version is discontinued. Well, ‘discontinued’ until I finally wrap my head around it… If you’re interested in solving this issue, and therefore, using nnetsauce for R, everything happens in this R script. You can submit a pull request (and star the repo 😉 )!

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