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This project is about explaining what machine learning classifiers (or models) are doing. At the moment, it supports explaining individual predictions for text classifiers or classifiers that act on tables (numpy arrays of numerical or categorical data) or images, with a package called lime (short for local interpretable model-agnostic explanations).

Uploaded Sun Mar 30 23:45:47 2025
md5 checksum c3274cc1032ca1984a542842b929cec8
arch x86_64
build py311h06a4308_0
depends matplotlib-base, numpy <2.0a0, python >=3.11,<3.12.0a0, scikit-image >=0.12, scikit-learn >=0.18, scipy, tqdm
license BSD-2-Clause
license_family BSD
md5 c3274cc1032ca1984a542842b929cec8
name lime
platform linux
sha1 0e946d63986ab853a864371ec74b04f0e8b95258
sha256 e9aa92276f4ede50d6db6c7cecd030f8aad991f68f78d846ec6b77828952283b
size 314652
subdir linux-64
timestamp 1692608686828
version 0.2.0.1