Nearest Instance Counterfactual Explanations (NICE)
NICE is an algorithm to generate Counterfactual Explanations for heterogeneous tabular data. Our approach exploits information from a nearest instance to speed up the search process and guarantee that an explanation will be found.
Installation
Install NICE through Pypi
pip install NICEx
or github
pip install git git+https://github.com/ADMantwerp/nice.git
Usage
NICE requires acces to the prediction score and trainingdata to generate counterfactual explanations.
from nice import NICE
# Initialize NICE by specifing the optimization strategy
NICE_explainer = NICE(optimization='sparsity')
# Fit our NICE explainer on the training data and classifier
NICE_explainer.fit(predict_fn,X_train,cat_feat,num_feat,y_train,optimization='sparsity')
# explain an instance
NICE_explainer.explain(x)
Examples
References
NICE: An Algorithm for Nearest Instance Counterfactual Explanations
1 maintainer
Metadata
1 maintainer
Release files for NICEx 0.2.3
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| NICEx-0.2.3.tar.gz | 8.9 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| NICEx-0.2.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 19.5 kB
Release files / NICEx-0.2.3.tar.gz
| Download URL | NICEx-0.2.3.tar.gz |
|---|---|
| Size | 8.9 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / NICEx-0.2.3-py3-none-any.whl
| Download URL | NICEx-0.2.3-py3-none-any.whl |
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| Size | 10.5 kB |
| Tags | Python 3 |
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