xcolumns 0.0.1

No project description provided

x Consistent Optimization of Label-wise Utilities in Multi-label classificatioN s

xCOLUMNs is a small Python library aims to implement different methods for optimization of general family of label-wise utilities (performance metrics) in multi-label classification, which scale to large (extreme) datasets.

Installation

The library can be installed using pip:

pip install xcolumns

It should work on all major platforms (Linux, Windows, Mac) and with Python 3.8+.

Repository structure

The repository is organized as follows:

• docs/ - Sphinx documentation (work in progress)
• experiments/ - a code for reproducing experiments from the papers
• xcolumns/ - Python package with the library

Methods, usage, and how to cite

The library implements the following methods:

Block Coordinate Ascent/Descent (BCA/BCD)

The method is described in the paper:

Erik Schultheis, Marek Wydmuch, Wojciech Kotłowski, Rohit Babbar, Krzysztof Dembczyński. Generalized test utilities for long-tail performance in extreme multi-label classification. NeurIPS 2023.

Frank-Wolfe (FW)

Description is work in progress.