Content:
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:
Examples of use of nnetsauce are available on GitHub, here (including R Markdown examples) and here.
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!
pip
at the command line for the stable versionpip install nnetsauce
conda
(Linux and macOS only for now)conda install -c conda-forge nnetsauce
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
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 )!