tda-representation-diagnostics

What problem does it solve?

This Skill provides diagnostic tools for checking embedding stability, scaler/PCA/loadings behavior, UMAP or t-SNE projections, observed/null coordinate-frame alignment, representation drift, and SHAP/feature explanations in TDL.

Core Features & Use Cases

• Embedding Stability: Check for stability in embeddings across different runs.
• Scaler/PCA/Loadings Behavior: Diagnose behavior of scalers, PCA, and loadings matrices.
• UMAP/t-SNE Projections: Validate UMAP or t-SNE projections for accurate representation.
• Coordinate Frame Alignment: Ensure observed and null data share a common fitted frame.
• Representation Drift: Detect changes in representation over time.
• SHAP/Feature Explanations: Provide associational explanations without causation claims.
• Use Case: When analyzing a complex dataset, use this Skill to diagnose issues in embeddings and representations, ensuring data accuracy and reliability.

Quick Start

Run the tda-representation-diagnostics skill on the dataset 'dataset.json' to check for representation drift and SHAP explanations.