Scikit-learn-style implementation of the close-k classifier.
This repository contains code accompanying
Bryan He, James Zou.
We provide a Python 3 implementation using the scikit-learn API, and provide code to reproduce the figures and tables from the paper.
Our package is available on PyPy, and can be installed using
pip install -i https://pypi.org/ closek
You can also install this package by cloning the Github repository, and running
pip install closek
If you want directly use the implementation in your package, you can also copy closek/closek.py into your code.
An example of how to use our package is shown in test.py.
Generating Results from Paper
The code used for the paper is in experiments. See the README there for more details.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size closek-1.0-py3-none-any.whl (4.8 kB)||File type Wheel||Python version py3||Upload date||Hashes View|
|Filename, size closek-1.0.tar.gz (3.4 kB)||File type Source||Python version None||Upload date||Hashes View|