rule_complete_report

Inputs

Outputs

from spl import SPLClient

result = SPLClient.embedded().call(
    "splime://@splime.project/case5-validation-20261011/rule_complete_report@1",
    kwargs={'dataset': 'replace-with-value', 'training_result': {}},
    trust=True,
)

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Evidence

Evidence-backed concepts

• Rule complete report
• Add application keyed predictions
• Evaluation partition labels
• Labels completed case5
• Case5 training report
• Scikit learn
• Key value mapping
• Structured JSON

• v111 Oct 20266 downloads

• rule_prepareValidate a prepared Case5 table and apply the chronological grouped search preset.
• rule_inspect_modelValidate and inspect a caller-supplied JSON rule model, classes, rules and feature schema.
• rule_monitorMonitor coverage and missing values. Pass optional target_col for labelled quality metrics.
• rule_predictScore a caller-supplied validated rule model without retraining or requiring a target.
• rule_searchCompare bounded interpretable structures with preprocessing and feature selection fitted independently within each CV train fold.