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/compute_fraud_by_month.Rd

@@ -0,0 +1,19 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/functions.R
+\name{compute_fraud_by_month}
+\alias{compute_fraud_by_month}
+\title{Fraud prevalence by month (counts + percent)}
+\usage{
+compute_fraud_by_month(in_prefix, use_duckdb = TRUE)
+}
+\arguments{
+\item{in_prefix}{Character. Dataset prefix inside the bucket, e.g. "03_primary/variant=Base".}
+
+\item{use_duckdb}{Logical. Use DuckDB for lazy querying. Default TRUE.}
+}
+\value{
+A tibble with Month, Fraud, Legit, Total, Pct_Fraud.
+}
+\description{
+Computes monthly counts of Fraud/Legit, totals, and percent fraud.
+}