Machine learning algorithms can be divided into two categories–statistic learning and
incremental learning algorithms. Incremental learning training set examples distribute over …

Streaming data has become an important form in the era of big data, and the concept drift, as
one of the most important problem of it, is often studied deeply. However, similar to true …

Nowadays changes happen with rapid rates. Technological changes and subsequent
changes in other aspects of life, the increasing interdependence of countries and peoples …

For achieving the adaptive learning, a predefined concept map of a course is often used to
provide adaptive learning guidance for learners. However, it is difficult and time consuming …

Concept lattice is a new mathematical tool for data analysis and knowledge processing.
Attribute reduction is very important in the theory of concept lattice because it can make the …

Accepted: 4 June 2019 Incremental learning refers to the learning of new information
iteratively without having to fully retain the classifier. However, a single classifier cannot …

The advent of cloud-computing has leads to evolution of collaborative state in Learning
Management System leading to re-defining the process of knowledge-delivery services in its …

Recent developments of computational intelligence on educational technology yield concept
map mining as a new research area. Concept map mining covers the extraction of learning …

An incremental learning algorithm based on weighted majority voting of an ensemble of
classifiers is introduced for supervised neural networks, where the voting weights are …

Incremental training has been used for genetic algorithm (GA)‐based classifiers in a
dynamic environment where training samples or new attributes/classes become available …