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r-lime

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When building complex models, it is often difficult to explain why the model should be trusted. While global measures such as accuracy are useful, they cannot be used for explaining why a model made a specific prediction. 'lime' (a port of the 'lime' 'Python' package) is a method for explaining the outcome of black box models by fitting a local model around the point in question an perturbations of this point. The approach is described in more detail in the article by Ribeiro et al. (2016) <arXiv:1602.04938>.

Installation

To install this package, run one of the following:

Conda
$conda install conda-forge::r-lime

Usage Tracking

0.5.4
0.5.3
0.5.2
0.5.1
0.5.0
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Downloads (Last 6 months): 0

About

Summary

When building complex models, it is often difficult to explain why the model should be trusted. While global measures such as accuracy are useful, they cannot be used for explaining why a model made a specific prediction. 'lime' (a port of the 'lime' 'Python' package) is a method for explaining the outcome of black box models by fitting a local model around the point in question an perturbations of this point. The approach is described in more detail in the article by Ribeiro et al. (2016) <arXiv:1602.04938>.

Last Updated

Dec 14, 2025 at 01:04

License

MIT

Total Downloads

91.2K

Version Downloads

522

Supported Platforms

win-64
macOS-64
linux-64