Zipf-Gramming: Scaling Byte N-Grams Up to Production Sized Malware Corpora

The Gini score is a widely used metric in statistical modeling and machine learning for validating and selecting models. Traditionally applied in binary contexts, it has equivalent formulations such as the receiver operating characteristic (ROC) and area under the curve (AUC). This paper discusses extending the Gini score to scenarios involving ties in risk rankings and adapting it for cases with weights, enhancing its applicability in actuarial contexts.