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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 23:45:46 2025
md5 checksum 34d78c8637d41ac5f48ed508dd3daacd
arch x86_64
build py310h06a4308_0
depends matplotlib-base, numpy <2.0a0, python >=3.10,<3.11.0a0, scikit-image >=0.12, scikit-learn >=0.18, scipy, tqdm
license BSD-2-Clause
license_family BSD
md5 34d78c8637d41ac5f48ed508dd3daacd
name lime
platform linux
sha1 bec09b5303b5f7912ab83eb890801f318d856815
sha256 5cf43f442b463ee50127005974087697021eaf15535f55d01ae686728f148143
size 291500
subdir linux-64
timestamp 1692608524672
version 0.2.0.1