rule_validate

Inputs

Outputs

from spl import SPLClient

result = SPLClient.embedded().call(
    "splime://@splime.project/case5-validation-20261011/rule_validate@1",
    kwargs={'categorical_cols': [], 'dataset': 'replace-with-value', 'exclude_cols': [], 'options': {}, 'target_col': 'replace-with-value', 'y': '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 validate
• Supply target col
• Split search options
• Optional exclusions
• Categorical columns
• Categorical cols
• Exclude cols
• Validate arbitrary supported classification table

• v111 Oct 20266 downloads

• 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_prepareValidate a prepared Case5 table and apply the chronological grouped search preset.
• rule_predictScore a caller-supplied validated rule model without retraining or requiring a target.
• rule_inspect_modelValidate and inspect a caller-supplied JSON rule model, classes, rules and feature schema.