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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 0e7820a3a4f3c23c986846c47757673f
arch x86_64
build py38h06a4308_0
depends matplotlib-base, numpy, python >=3.8,<3.9.0a0, scikit-image >=0.12, scikit-learn >=0.18, scipy, tqdm
license BSD-2-Clause
license_family BSD
md5 0e7820a3a4f3c23c986846c47757673f
name lime
platform linux
sha1 90d401a15aaea0c0b470016dda338050d5acbea8
sha256 51bf36cb48b8e97d278917166b157a040ddd4158e7e7989f157672921e61ebc4
size 291483
subdir linux-64
timestamp 1692608430361
version 0.2.0.1