mdhabibi/LIME-for-Time-Series
LIME for TimeSeries enhances AI transparency by providing LIME-based interpretability tools for time series models. It offers insights into model predictions, fostering trust and understanding in complex AI systems.
No commits in the last 6 months.
Stars
15
Forks
3
Language
Jupyter Notebook
License
GPL-3.0
Last pushed
Mar 23, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mdhabibi/LIME-for-Time-Series"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
obss/sahi
Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
MAIF/shapash
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent...
SeldonIO/alibi
Algorithms for explaining machine learning models
understandable-machine-intelligence-lab/Quantus
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.