gds-sphere-designer

Sphere design for anomaly detection involves discovering data, defining patterns, generating a sphere.yaml configuration, building geometry, and calibrating models iteratively to achieve actionable anomaly detection results.

Structuring data discovery and pattern strategy requires a phased workflow spanning discovery, design, build, and verification, leveraging reference materials for domain patterns to ensure navigable geometry.

Isolating orthogonal concerns during geometry build uses NB-Split isolation strategies to separate concerns onto distinct entity lines, preserving signal integrity and enabling cross-pattern scoring.

Yes, reusing established design patterns via reference-driven domain materials accelerates sphere creation, enabling rapid generation and comparison of geometric sphere configurations.

Yes, providing a sphere.yaml file describing your data sources and patterns is required to run the build process and generate, calibrate, and verify the geometric sphere.

Avoid using a single entity line for multiple geometric patterns when signal preservation and cross-pattern scoring are critical; instead, apply NB-Split isolation strategies to separate orthogonal concerns onto distinct entity lines.