Rob Wiederstein
33d0fc31c7
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>
20 lines
595 B
R
20 lines
595 B
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/functions.R
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\name{compute_fraud_by_month}
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\alias{compute_fraud_by_month}
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\title{Fraud prevalence by month (counts + percent)}
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\usage{
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compute_fraud_by_month(in_prefix, use_duckdb = TRUE)
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}
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\arguments{
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\item{in_prefix}{Character. Dataset prefix inside the bucket, e.g. "03_primary/variant=Base".}
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\item{use_duckdb}{Logical. Use DuckDB for lazy querying. Default TRUE.}
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}
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\value{
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A tibble with Month, Fraud, Legit, Total, Pct_Fraud.
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}
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\description{
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Computes monthly counts of Fraud/Legit, totals, and percent fraud.
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}
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