… to predicting performance based on students’ digital records collected from online learning
… : Examining the intercorrelations and the incremental validity of narrow traits.Journal of …

… prediction performance. In addition, it is an instance-based learning algorithm where
incremental learning … Another accuracy metric is prepared to evaluate the performance based on …

… Stevens et al., studying the performance of ANN-based modelling included a combinational
incremental ensemble classifier to predict student performances in distance education [34]. …

… Different layers of the network obtain a different number of parameters representing learned
features, however it is difficult to predict at what point of incremental learning a layer will not …

… model f(·) that takes an image as input and outputs the class predictions. For an … the top-k
most similar base classes. During the incremental learning phases, we utilize these Gaussian …

… In this study, the classification model is able to predict students’ procrastination at the
start of the semester, enabling course instructors to take remedial actions before it is too late. …

… prediction as an incremental learning problem, we propose an incremental travel time predictor…
the catastrophic forgetting issue for the incremental predictor by distilling and transferring …

… In [17], the author in his research aimed to develop an algorithm with incremental learning
to mine data flows that is capable of manipulating gradual, abrupt or recurrent concept …

… prediction model of students’ academic performance based on their interaction with learning
… system in order to explore the performance of Random Forest in the prediction of student …

… parameters dynamically based on task relevance, achieving improved prediction accuracy.
… under supervised learning, while our approach involves incremental learning within a semi-…