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 …

Accurate flight delay prediction is fundamental to establish the more efficient airline
business. Recent studies have been focused on applying machine learning methods to …

According to the development of deep learning technologies, a wide variety of research is
being performed to detect intrusion data by using vast amounts of data. Although deep …

Imbalanced datasets pose significant challenges in areas including neuroscience, cognitive
science, and medical diagnostics, where accurately detecting minority classes is essential …

Pairwise learning is an important machine-learning topic with many practical applications.
An online algorithm is the first choice for processing streaming data and is preferred for …

Extreme learning machines (ELMs) has been theoretically and experimentally proved to
achieve promising performance at a fast learning speed for supervised classification tasks …

Abstract Semantics-aware anomaly detection based on log has attracted much attention.
However, the existing methods based on the weighted aggregation of all word vectors might …

The evaluation of deep-learning (DL) systems typically relies on the Area under the
Receiver-Operating-Curve (AU-ROC) as a performance metric. However, AU-ROC, in its …

Deep recurrent neural networks have been successfully applied to knowledge tracing,
namely, deep knowledge tracing (DKT), which aims to automatically trace students' …

For over two decades, detecting rare events has been a challenging task among
researchers in the data mining and machine learning domain. Real-life problems inspire …