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Linear Regression with numpy only.

Project description


# numpy-linreg Linear Regression with numpy only.

## Installation The numpy-linreg [git repo]( is available as [PyPi package](

` pip install numpy-linreg pip install git+ssh:// `

## Usage Ridge Regression

` import numpy_linreg.ridge as ridge import numpy_linreg.metrics as metrics beta =, X) rmse = metrics.rmse(y, X, beta) `

OLS Regression

` import numpy_linreg.ols as ols beta =, X) beta = ols.pinv(y, X) beta = ols.qr(y, X) beta = ols.svd(y, X) `

Check the [examples]( folder for notebooks.

## Commands Install a virtual environment

` python3.6 -m venv .venv source .venv/bin/activate pip3 install --upgrade pip pip3 install -r requirements.txt `

(If your git repo is stored in a folder with whitespaces, then don’t use the subfolder .venv. Use an absolute path without whitespaces.)

Python commands

  • Jupyter for the examples: jupyter lab
  • Check syntax: flake8 –ignore=F401 –exclude=$(grep -v ‘^#’ .gitignore | xargs | sed -e ‘s/ /,/g’)
  • Upload to PyPi with twine: python sdist && twine upload -r pypi dist/*

Clean up

` find . -type f -name "*.pyc" | xargs rm find . -type d -name "__pycache__" | xargs rm -r rm -r .pytest_cache rm -r .venv `

## Support Please [open an issue]( for support.

## Contributing Please contribute using [Github Flow]( Create a branch, add commits, and [open a pull request](

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