rkw/bank-fraud-baf-lakehouse
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85bc257e7bc6fd250fd21b619b25e39bac1ad9ff
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4 Commits

Author SHA1 Message Date
Rob Wiederstein
85bc257e7b Rename package from baflakehouse to bankfraud
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- DESCRIPTION: Package name and URL updated to /bank-fraud
- R/baflakehouse-package.R → R/bankfraud-package.R
- _pkgdown.yml: url and reference alias updated
- deploy.yaml: TARGET_DIR updated to /var/www/docs/bank-fraud/
- deploy/baflakehouse.caddy: deleted (stale, superseded by rsync workflow)
- tests and README updated

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-02-23 09:38:54 -05:00
Rob Wiederstein
b38892f49e Refactor: consistent naming across functions, targets, and pkgdown 
Functions: prepare_eda_recipe -> build_eda_recipe,
           create_efficiency_plot -> plot_efficiency,
           format_class_imbalance_tourney_gt -> format_tournament_gt

Targets: model_inputs_prefix -> baf_model_input_prefix,
         tbl_fraud_by_month_data -> fraud_by_month_summary,
         model_diag -> diag_fit, winning_params -> best_params,
         production_recipe_blueprint -> prod_recipe,
         final_eval_data -> test_predictions

pkgdown: restructured reference index into 6 logical sections,
         removed stale names and development comments.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-02-22 03:52:34 -05:00
Rob Wiederstein
f47b2e1be2 Add tune_lgbm() and wire hyperparameter tuning into DAG 
Converts scratch/tune_model.R into a pure tune_lgbm() function,
replacing hardcoded winning_params with a fully automated tar_target.
Best params (trees=844, depth=3, lr=0.0204, min_n=389) now flow
reproducibly into evaluate_final_model() and train_production_model().
PR-AUC improved from 0.165 to 0.198.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-02-22 03:25:35 -05:00
Rob Wiederstein
33d0fc31c7 Initial commit: BAF Lakehouse fraud detection pipeline 
End-to-end LightGBM fraud detection pipeline built as an R package,
orchestrated by targets with data stored in MinIO via Apache Arrow.
Includes 6-layer Lakehouse architecture, class imbalance tournament,
formally tuned hyperparameters (PR-AUC 0.198), and Quarto RevealJS slides.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-02-21 21:19:09 -05:00