Machine Learning Assessment: implications to cybersecurity. (arXiv:1907.12851v4 [stat.ML] UPDATED)

This chapter is dedicated to the assessment and performance estimation of
machine learning (ML) algorithms, a topic that is equally important to the
construction of these algorithms, in particular in the context of cyberphysical
security design. The literature is full of nonparametric methods to estimate a
statistic from just one available dataset through resampling techniques, e.g.,
jackknife, bootstrap and cross validation (CV). Special statistics of great
interest are the error rate and the area under the ROC curve (AUC) of …

arxiv cybersecurity learning machine machine learning ml