Instance selection is a feasible strategy to solve the problem of dealing with large databases
in inductive learning. There are several proposals in this area, but none of them consistently …

Graduating on time at the higher education level is one of the main targets of every student
and university institution. Many factors can affect a student's length of study, the different …

Classification techniques used in Educational System Page 1 Classification techniques used in
Educational System Elena Şuşnea National Defence University "Carol I", Bucharest, 68-72 …

Basic classification algorithms induce a single model from training data. The interpretation of
a model is relatively easy, while basic algorithms have limitations in achieving high …

Education Data Mining has taken a big leap in the area of research. Several researcher
scholars have taken Education Data Mining to the next level through their research findings …

Currently the challenges in e-Learning are converging the learning content from various
sources and managing them within e-learning practices. Data mining learning algorithms …

Researchers, teachers, librarians, and individuals in daily practice perform various activities
that require the processing of large amounts of knowledge and dynamic information flow …

In this paper we compare the accuracy of data mining methods to classifying students in
order to predicting student's class grade. These predictions are more useful for identifying …

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 …

A prime objective in constructing data streaming mining models is to achieve good accuracy,
fast learning, and robustness to noise. Although many techniques have been proposed in …