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>

man/clean_baf_base.Rd

@@ -0,0 +1,34 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/functions.R
+\name{clean_baf_base}
+\alias{clean_baf_base}
+\title{Clean the BAF Base dataset and write to 03_primary}
+\usage{
+clean_baf_base(
+  in_prefix,
+  out_prefix = "03_primary/variant=Base",
+  bucket_name = "baf-fraud",
+  partitioning = "month",
+  existing_data_behavior = c("overwrite", "error", "delete_matching"),
+  verbose = TRUE
+)
+}
+\arguments{
+\item{in_prefix}{Character. Input dataset prefix inside bucket (e.g. "02_intermediate/variant=Base").}
+
+\item{out_prefix}{Character. Output dataset prefix inside bucket (e.g. "03_primary/variant=Base").}
+
+\item{bucket_name}{Character. Bucket name. Default "baf-fraud".}
+
+\item{partitioning}{Character vector of columns to partition by. Default "month". Set NULL to disable.}
+
+\item{existing_data_behavior}{One of "overwrite", "error", "delete_matching". Default "overwrite".}
+
+\item{verbose}{Logical. Emit progress messages. Default TRUE.}
+}
+\value{
+Character. out_prefix (for downstream targets).
+}
+\description{
+Clean the BAF Base dataset and write to 03_primary
+}