rule_prepare

Inputs

Outputs

from spl import SPLClient

result = SPLClient.embedded().call(
    "splime://@splime.project/case5-validation-20261011/rule_prepare@1",
    kwargs={'dataset': 'replace-with-value', '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 prepare
• Apply chronological grouped search preset
• Target col
• Validate prepared case5 table
• Scikit learn
• Key value mapping
• Structured JSON
• Numerical arrays

• v111 Oct 20266 downloads

• rule_validateValidate an arbitrary supported classification table. Supply target_col or y; optional exclusions, categorical columns and split/search options.
• rule_monitorMonitor coverage and missing values. Pass optional target_col for labelled quality metrics.
• 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_complete_reportAdd application-keyed predictions and evaluation partition labels to a completed Case5 training report.
• rule_inspect_modelValidate and inspect a caller-supplied JSON rule model, classes, rules and feature schema.