pipelineVerified releasev1
rule_search
Compare bounded interpretable structures with preprocessing and feature selection fitted independently within each CV train fold.
Interface
Verified contract
Inputs
| Name | Type |
|---|---|
| split | dict |
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_search@1",
kwargs={'split': {}},
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 search
- Compare bounded interpretable structures
- Feature selection fitted
- Fitted independently each
- Each cv train
- Scikit learn
- Key value mapping
- Structured JSON
History
Public versions
- v16 downloads
Discover
Similar Objects
- rule_inspect_modelValidate and inspect a caller-supplied JSON rule model, classes, rules and feature schema.
- rule_evaluateEvaluate a fixed fitted model on development and independent holdout without changing the selected rules.
- rule_fitFit the selected configuration using development data only.
- rule_splitCreate development/holdout/CV partitions from validated state, respecting configured time and group boundaries.
- rule_complete_reportAdd application-keyed predictions and evaluation partition labels to a completed Case5 training report.