# SMX ```{raw} html

Spectral Model eXplainer

Explain spectral ML models with zone-level predicates

SMX is a global, model-agnostic explainer for spectral classifiers. It turns spectra into expert zones, generates logical predicates, and ranks them with a graph-based centrality score.

``` ## What SMX provides - End-to-end pipeline via the `SMX` class - Zone extraction and PCA aggregation tailored to spectral inputs - Quantile predicates with bagging and perturbation-based ranking - Directed predicate graph with Local Reaching Centrality (LRC) - Natural-scale threshold reconstruction and Plotly visuals - Faithfulness evaluation with progressive masking ::::{grid} 3 :::{grid-item-card} Quickstart :link: quickstart :link-type: doc Run SMX end to end on a synthetic dataset in minutes. ::: :::{grid-item-card} Pipeline :link: pipeline :link-type: doc Understand how zones, predicates, and graphs fit together. ::: :::{grid-item-card} Plotting Gallery :link: plotting :link-type: doc Explore the full suite of SMX visualization helpers. ::: :::{grid-item-card} API Reference :link: api_reference :link-type: doc Auto-generated reference for every public module. ::: :::{grid-item-card} Examples :link: examples :link-type: doc Scripts and notebooks shipped with the repository. ::: :::{grid-item-card} Repository Map :link: repository :link-type: doc A guided tour of the SMX source tree. ::: :::: ## Contents ```{toctree} :maxdepth: 2 :caption: User Guide installation quickstart pipeline zones predicates graph faithfulness plotting datasets examples repository ``` ```{toctree} :maxdepth: 2 :caption: API Reference api_reference ```