Seizure prediction remains a challenge, with approximately 30% of patients unresponsive to
conventional treatments. Addressing this issue is crucial for improving patients' quality of life …

As many real data sets (eg, social, financial, and medical data sets) are successively
generated in evolution with the ever-changing environment, classification for data stream …

A two-step approach is presented for anomaly detection and diagnosis in batch process
systems. The approach was applied to a case study of a decontamination process in …

There is an increasing interest in the use of AI in healthcare due to its potential for diagnosis
or disease prediction. However, healthcare data is not static and is likely to change over time …

The dynamic nature and time-varying behavior of actual environments provide serious
challenges for learning models. Thus, changes may deteriorate the constructed control …

Last decade demonstrate the massive growth in organizational data which keeps on
increasing multi‐fold as millions of records get updated every second. Handling such vast …

Abstract Concept drift poses significant challenges in the fields of machine learning and data
mining. At present, many existing algorithms struggle to maintain low error rates or require …

In this paper we describe the application of a learning classifier system (LCS) variant known
as the eXtended classifier system (XCS) to evolve a set of 'control rules' for a number of …

在开放环境下, 数据流具有数据高速生成, 数据量无限和概念漂移等特性. 在数据流分类任务中,
利用人工标注产生大量训练数据的方式昂贵且不切实际. 包含少量有标记样本和大量无标记样本 …