The dynamicity of real-world systems poses a significant challenge to deployed predictive
machine learning (ML) models. Changes in the system on which the ML model has been …

Developing effective and efficient data stream classifiers is challenging for the machine
learning community because of the dynamic nature of data streams. As a result, many data …

Classification plays a crucial role in mining the evolving data streams. The concept drift and
concept evolution are the major issues of data streams classification, which greatly affect the …

In this study, we focus on semi-supervised data stream classification tasks. With the advent
of applications that generate vast streams of data, data stream mining algorithms are …

Buildings are currently among the largest consumers of electrical energy with considerable
increases in CO2 emissions in recent years. Although there have been notable advances in …

Many dynamic processes in the real world can be modeled as time series, so time series
prediction is significant for social and economic development. The inherent non-stationarity …

Advances over the past decade at the intersection of information fusion methods and Semi-
Supervised Learning (SSL) are investigated in this paper that grapple with challenges …

Nitrogen is an essential nutrient element for the growth of citrus tree. The accurate
estimation of leaf nitrogen content (LNC) is important to guarantee fruit quality and yield. The …

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 …

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 …