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"""seqeval — budgeted, anytime-valid sequential regression detection.
Detects small (~2pp) per-stratum model regressions without evaluating the full
corpus, with validity under sequential looks, clustering, stratification and
multiple comparisons. See DESIGN.md in this package for the full statistical
design and its justifications.
Module map:
units.py statistical units: clusters, ICC, design effect
planner.py frozen stratified sampling plans (Neyman + risk floors)
paired.py paired harness + fingerprint-keyed prediction cache
sequential.py empirical-Bernstein confidence sequences, e-processes,
three-outcome decisions, Beta-Binomial complement
hierarchy.py hierarchical gatekeeping with e-BH within levels
attribution.py the regression map
ledger.py machine-readable evidence records + lineage
controller.py sanity -> screening -> sequential -> escalation state machine
api.py REST surface under /api/seqeval
Entry point for the safety Regression Gate:
from sensorflow.seqeval import evaluate_regression
"""
from sensorflow.seqeval.controller import evaluate_regression # noqa: F401