… of incremental learning approaches in processing massive data in real time, we propose an
incremental learning based … of incremental learning to make predictions and update models: …

… Hence the research objective of the study is to improve prediction performance and help to …
for the student data set. As we all know incremental learning may be a learning mechanism in …

… The studies that are focused on predicting student performance can be … predict student
performance based on students’ demographic data, their personality, or other survey-based …

… world datasets of faces and natural scenes in comparison with direct attribute prediction and
semi-supervised learning approaches, and a noteworthy performance increase is achieved. …

… incremental learning paradigm called Deep Model Consolidation (DMC), which works well
even when the original training … In this way, we encourage the predicted bounding box of the …

… behavior and develop interventions for struggling students. This study used student data
stored in a Moodle server and predicted student success in course, based on four learning …

… We present a novel class incremental learning approach based on deep neural networks,
which continually learns new tasks with limited memory for storing examples in the previous …

… performance of Genetic Algorithm and Population-based Incremental Learning algorithm
on a student … The proposed student ranking application focuses on proving the students’ …

… this study was to construct a model for predicting students’ academic performance based
on … are suitable for predicting students’ academic performance?), this study applied eight …

… building a model for predicting student’s performance. The results using … incremental
ensemble of classifiers as a technique for predicting students’ performance in distance education …