Skip to main content

tshap

A SHAP-based attribution method for time series classification and regression.

This repo accompanies our ECML-PKDD 2025 research track paper TSHAP: Fast and Exact SHAP for Explaining Time Series Classification and Regression.

Citation

If you use this repository in your research, please cite as:

@misc{lenguyen2025tshap,
    title={[TSHAP: Fast and Exact SHAP for Explaining Time Series Classification and Regression},
    author={Thach Le Nguyen and Georgiana Ifrim},
    year={2025},
    conference={ECMLPKDD},
    eprint={https://www.researchgate.net/publication/392833501_TSHAP_Fast_and_Exact_SHAP_for_Explaining_Time_Series_Classification_and_Regression},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

Metadata

Release files for tshap 0.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for tshap 0.0.1
File Size Uploaded Provenance Actions
tshap-0.0.1.tar.gz 19.2 kB Without provenance Details for tshap-0.0.1.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for tshap 0.0.1
File Interpreter ABI Platform Actions
tshap-0.0.1-py3-none-any.whl Python 3 none any Details for tshap-0.0.1-py3-none-any.whl

Total release size: 38.5 kB

Release files / tshap-0.0.1.tar.gz

Download URL tshap-0.0.1.tar.gz
Size 19.2 kB
Tags Source
SHA-256 checksum
How to use checksums
66d71c09f8ff0b6614c702be3299043ee79dd52ec3569bb4b37c6186c1016f7d
BLAKE2b-256 checksum
How to use checksums
42d27a26e1e6ea33652691a67dea85243aa6fcc51b0ce4c20bdb7f6f3de7c4dd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.10.0

Release files / tshap-0.0.1-py3-none-any.whl

Download URL tshap-0.0.1-py3-none-any.whl
Size 19.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
257c879882e61e63ae3ce1e4841b998e855fc95e899426446fadc39a33678b09
BLAKE2b-256 checksum
How to use checksums
8ad9a5366423bdb2ade9af65e2770a740e483f617ea3af5093fc5458a23cd630
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.10.0

Security for tshap 0.0.1

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.0.1 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page