pipelineVerified releasev1
rule_monitor
Monitor coverage and missing values. Pass optional target_col for labelled quality metrics.
Interface
Verified contract
Inputs
| Name | Type |
|---|---|
| model | dict |
| dataset | unspecified |
| target_col | str | None |
Outputs
| Name | Type |
|---|---|
| result | unspecified |
Exact release
Pinned local call
from spl import SPLClient
result = SPLClient.embedded().call(
"splime://@splime.project/case5-validation-20261011/rule_monitor@1",
kwargs={'dataset': 'replace-with-value', 'model': {}, 'target_col': 'replace-with-value'},
trust=True,
)Review before running. Public bundles contain executable code. Verify the publisher and exact content hash; a virtual environment isolates dependencies, not the operating system.
Evidence
Evidence-backed concepts
- Rule monitor
- Labelled quality metrics
- Missing values
- Monitor coverage
- Target col
- Pass optional target
- Scikit learn
- Key value mapping
History
Public versions
- v17 downloads
Discover
Similar Objects
- rule_validateValidate an arbitrary supported classification table. Supply target_col or y; optional exclusions, categorical columns and split/search options.
- rule_prepareValidate a prepared Case5 table and apply the chronological grouped search preset.
- find_rulesSearch numeric classification rules with a dataset and target column. Skip unsupported columns and return their names and reasons in unusable_columns, alongside the model, predictions and holdout metrics.
- rule_predictScore a caller-supplied validated rule model without retraining or requiring a target.
- rule_complete_reportAdd application-keyed predictions and evaluation partition labels to a completed Case5 training report.