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EarlyStopping: Implicit Regularisation for Iterative Learning Procedures in Python

Project description

Early stopping

Early stopping is a python library implementing computationally efficient model selection methods for iterative estimation procedures based on the theory in

Check out the documentation for more information.

Development notes

Installation for development

Required dependencies: git, Python3, JupyterNotebooks.

Manual setup:

python3 -m pip install build virtualenv               # Install build tools
git clone https://github.com/ESFIEP/EarlyStopping.git # Clone git repository
python3 -m build                                      # Build package
python3 -m venv myenv                                 # Create virtual environment
source myenv/bin/activate                             # Activate virtual environment
python3 -m pip install numpy ipykernel                # Install python packages to the environment
python3 -m pip install -e .                           # Install the EarlyStopping package in editable mode
python3 -m ipykernel install --user --name=myenv      # Create Jupyter kernel from the environment

From the notebooks directory open the Jupyter notebook example.ipynb with the kernel myenv and run the code!

Installation from Python Package Index

https://test.pypi.org/project/EarlyStopping

Creating documentation locally

The online documentation is not built until it has been merged into main. To build documentation locally and check how things look run

sphinx-build -M html docs/source docs/build

in the EarlyStopping directory. The documentation will be generated in docs/build/html. To view them locally open index.html with firefox or another browser. Information about about documenting projects with sphinx.

Under Linux, it was necessary to include

import os
import sys
sys.path.insert(0, os.path.abspath('../../src'))

in docs/source/conf.py. Please only include this locally and never push the change.

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