dime-xai 1.2.1

Explains DIETClassifier model predictions in Rasa chatbot framework.

DIME (Dual Interpretable Model-agnostic Explanations) is mainly aimed at Explaining DIET Classifiers in RASA 2.8.X. Models.

Features 🦄

• Explains RASA DIET Classifiers using feature importance
• Generates dual feature importance scores (Global FI + Local FI)
• Efficient
• Total confidence drop as the feature importance score
• Able to explain both local and REST Rasa models
• Easy to use DIME CLI
• GUI with a dedicated server on-demand
• Generate, Store, Download, Upload, Peak DIME explanations. Read more on docs
• Supports Sinhalese unicode / fully Sinhala-English code-switchable

What's Cooking? 🍪

• DIME for Jupyter Notebooks
• Stopwords List Generation
• DIME Example Notebooks
• DIME for non-DIET text classification models

Limitations and Known Issues 🤏🏽

• Global Importance is disabled for REST models due to performance bottlenecks
• Explaining RASA models locally on Notebooks such as CoLab is not supported yet due to dependency issues
• Benchmark tests are in progress

📒 Docs: https://dime-xai.github.io
📦 PyPi: https://pypi.org/project/dime-xai/1.2.1/
🪵 Full Changelog: https://github.com/DIME-XAI/dime-xai/blob/main/CHANGELOG.md