… strategy changes, the quick increment of Chinese undergraduate … They trained an ensemble
of classification models from … features to enhance classification and prediction accuracy, in …

… are ensemble learning methods that improve classification … a career guidance system based
on the ANN MLP classifier … predictions for students and users exploring career options. The …

… Forest, Bagging, an ensemble methodology, and a vertical … a decision tree for tuples that do
not provide classification labels, … increment value of all indicators to generate a decision tree. …

… labeled student data and the training of a classification … the trained algorithm to predict the
ranks of students’ semester … the clustering method effective for incremental and dynamic data. …

… [33] combined an incremental version of Naive Bayes, the 1-… Zhang [40] improved the
decision tree classification method … a heterogeneous ensemble classifier configuration based on …

… , it suggests a new stacking ensemble in this study that is based … classification of and
comparative analysis of various student … Fuzzy ARTMAP is used in incremental supervised …

… a reliable and comprehensible classification model with a … probabilistic ensemble simplified
fuzzy and decision scheme… Cohen as an optimized version of Incremental Reduced Error …

… built a classification model based on the GBM for each dataset to predict student performance,
… method to improve the accuracy of conventional classifiers and therefore maximize the …

… outcomes called "the combinational incremental ensemble of classifiers". Three … Xenos,
“A combinational incremental ensemble of classifiers as a technique for predicting students’ …

… decision trees is illustrated, and it will lay down the required foundation for later chapters.
Bagging of decision trees and k-NN classifiers … As such, we consider the new predicted …