Skip to main content

✂️ Fast slice finding for Machine Learning model debugging.

Project description

Sliceline is a Python library for fast slice finding for Machine Learning model debugging.

It is an implementation of SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging, from Svetlana Sagadeeva and Matthias Boehm of Graz University of Technology.

👉 Getting started

Given an input dataset X and a model error vector errors, SliceLine finds the top slices in X that identify where a ML model performs significantly worse.

You can use sliceline as follows:

from sliceline.slicefinder import Slicefinder

slice_finder = Slicefinder()

slice_finder.fit(X, errors)

print(slice_finder.top_slices_)

X_trans = slice_finder.transform(X)

We invite you to check the demo notebooks for a more thorough tutorial:

  1. Implementing Sliceline on Titanic dataset

  2. Implementing Sliceline on California housing dataset

🛠 Installation

Sliceline is intended to work with Python 3.7 or above. Installation can be done with pip:

pip install sliceline

There are wheels available for Linux, MacOS, and Windows, which means that you most probably won’t have to build Sliceline from source.

You can install the latest development version from GitHub as so:

pip install git+https://github.com/DataDome/sliceline --upgrade

Or, through SSH:

pip install git+ssh://git@github.com/datadome/sliceline.git --upgrade

👐 Contributing

Feel free to contribute in any way you like, we’re always open to new ideas and approaches.

  • Open a discussion if you have any question or enquiry whatsoever. It’s more useful to ask your question in public rather than sending us a private email. It’s also encouraged to open a discussion before contributing, so that everyone is aligned and unnecessary work is avoided.

  • Feel welcome to open an issue if you think you’ve spotted a bug or a performance issue.

Please check out the contribution guidelines if you want to bring modifications to the code base.

📝 License

Sliceline is free and open-source software licensed under the 3-clause BSD license.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sliceline-0.2.14.tar.gz (18.2 kB view details)

Uploaded Source

Built Distribution

sliceline-0.2.14-py3-none-any.whl (18.0 kB view details)

Uploaded Python 3

File details

Details for the file sliceline-0.2.14.tar.gz.

File metadata

  • Download URL: sliceline-0.2.14.tar.gz
  • Upload date:
  • Size: 18.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.9.19 Linux/6.5.0-1023-azure

File hashes

Hashes for sliceline-0.2.14.tar.gz
Algorithm Hash digest
SHA256 5c01ce36415d251c379e9492558022c81937fe492ef66101bed66ff029825d71
MD5 e34f0251f5957eac7de6a640a9325c98
BLAKE2b-256 0fd89cdc2e6cf2512e15012703097add8a38489432b3a1bf1e1015fa915a903e

See more details on using hashes here.

File details

Details for the file sliceline-0.2.14-py3-none-any.whl.

File metadata

  • Download URL: sliceline-0.2.14-py3-none-any.whl
  • Upload date:
  • Size: 18.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.9.19 Linux/6.5.0-1023-azure

File hashes

Hashes for sliceline-0.2.14-py3-none-any.whl
Algorithm Hash digest
SHA256 a9e511706cc720b0b35e80019769c41d4f20b9c7f7fbc926ac1993d3c155ccd2
MD5 7faaca4941fb1b1262c183d61f3cd4e2
BLAKE2b-256 37f272103ed2fec9850a78f6e5646fadf42fface26e7ebf0ccf93730c5833530

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page