Area under the ROC curve, aka AUC, is a measure of choice for assessing the performance
of a classifier for imbalanced data. AUC maximization refers to a learning paradigm that …

Phishing attacks are a type of cybercrime that has grown in recent years. It is part of social
engineering attacks where an attacker deceives users by sending fake messages using …

An up-to-date, self-contained introduction to a state-of-the-art machine learning approach,
Ensemble Methods: Foundations and Algorithms shows how these accurate methods are …

The field of machine learning has matured to the point where many sophisticated learning
approaches can be applied to practical applications. Thus it is of critical importance that …

Predicting the occurrence of links is a fundamental problem in networks. In the link
prediction problem we are given a snapshot of a network and would like to infer which …

Receiver Operator Characteristic (ROC) curves are commonly used to present results for
binary decision problems in machine learning. However, when dealing with highly skewed …

Face manipulation techniques, especially DeepFake techniques, are causing severe social
concerns and security problems. When faced with skewed data distributions such as those …

The quality measures used in information retrieval are particularly difficult to optimize
directly, since they depend on the model scores only through the sorted order of the …

This paper presents a Support Vector Method for optimizing multivariate nonlinear
performance measures like the F 1-score. Taking a multivariate prediction approach, we …

The area under an ROC curve (AUC) is a criterion used in many applications to measure the
quality of a classification algorithm. However, the objective function optimized in most of …