SPLime Public Hub

Discover useful Python Objects.

Browse verified, versioned Functions, Pipelines, and Library Adapters. Inspect the contract, pin an exact release, and run it with the SPLime framework.

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Verified releases

14 shown
pipelinev4

find_rules

Search 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.

@splime.projectcase5-validation-20261011
CallableScore 038 downloads
pipelinev3

case5_first_pd1_model

Retrieve the fitted first_pd1 JSON model, exact rules and input schema embedded in this immutable release.

@splime.projectcase5-validation-20261011
CallableScore 06 downloads
pipelinev3

case5_first_pd1_predict

Apply the fitted first_pd1 rules embedded in this release. Returns application IDs, predicted classes, probabilities and segments. No caller-side model file or retraining is required.

@splime.projectcase5-validation-20261011
CallableScore 06 downloads
pipelinev1

rule_complete_report

Add application-keyed predictions and evaluation partition labels to a completed Case5 training report.

@splime.projectcase5-validation-20261011
CallableScore 06 downloads
pipelinev1

rule_evaluate

Evaluate a fixed fitted model on development and independent holdout without changing the selected rules.

@splime.projectcase5-validation-20261011
CallableScore 06 downloads
pipelinev1

rule_finalize

Produce a JSON model, exact rules, leaderboard, metrics and audit; omit the intermediate training table.

@splime.projectcase5-validation-20261011
CallableScore 06 downloads
pipelinev1

rule_fit

Fit the selected configuration using development data only.

@splime.projectcase5-validation-20261011
CallableScore 06 downloads
pipelinev1

rule_inspect_model

Validate and inspect a caller-supplied JSON rule model, classes, rules and feature schema.

@splime.projectcase5-validation-20261011
CallableScore 08 downloads
pipelinev1

rule_monitor

Monitor coverage and missing values. Pass optional target_col for labelled quality metrics.

@splime.projectcase5-validation-20261011
CallableScore 07 downloads
pipelinev1

rule_predict

Score a caller-supplied validated rule model without retraining or requiring a target.

@splime.projectcase5-validation-20261011
CallableScore 010 downloads
pipelinev1

rule_prepare

Validate a prepared Case5 table and apply the chronological grouped search preset.

@splime.projectcase5-validation-20261011
CallableScore 06 downloads
pipelinev1

rule_search

Compare bounded interpretable structures with preprocessing and feature selection fitted independently within each CV train fold.

@splime.projectcase5-validation-20261011
CallableScore 06 downloads
pipelinev1

rule_split

Create development/holdout/CV partitions from validated state, respecting configured time and group boundaries.

@splime.projectcase5-validation-20261011
CallableScore 06 downloads
pipelinev1

rule_validate

Validate an arbitrary supported classification table. Supply target_col or y; optional exclusions, categorical columns and split/search options.

@splime.projectcase5-validation-20261011
CallableScore 06 downloads