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hub / github.com/Open-Quant/openquant / _standardize

Function _standardize

python/openquant/feature_diagnostics.py:457–467  ·  view source on GitHub ↗
(x: Sequence[Sequence[float]])

Source from the content-addressed store, hash-verified

455 table = _importance_table(names, per_feature)
456 payload = viz.prepare_feature_importance_payload(
457 table["feature"].to_list(), table["mean"].to_list(), std=table["stderr"].to_list()
458 )
459 return {
460 "method": "sfi",
461 "table": table,
462 "records": table.to_dicts(),
463 "viz_payload": payload,
464 "cv": {
465 "method": "purged_kfold" if event_end_indices is not None else "kfold_embargo_only",
466 "purged": event_end_indices is not None,
467 "n_splits": n_splits,
468 "pct_embargo": pct_embargo,
469 "fold_count": len(splits),
470 "scoring": scoring,

Callers 2

_corr_matrixFunction · 0.85

Calls 2

maxFunction · 0.85
appendMethod · 0.80

Tested by

no test coverage detected