… To this aim, in this paper we propose a strategy based on ensemble learning in order to …
a stacking ensemble learning scheme, where the predictions produced by three base learning …

… In this paper, we propose stacked ensemble learning model for network intrusion detection
by using gradient boosting machine (GBM) and random forest (RF) algorithms. The proposed …

… Thus, this study evaluates an ensemble learning model that combines bagging and stacking
methods applied to … 3 illustrates the stacking ensemble learning workflow used in this paper. …

… of stacking ensemble learning with the use of VA. In this section, we briefly discuss previous
works on bagging, boosting, and buckets of models, and highlight their differences with …

… In this paper, we propose a multilayered stacked ensemble learning technique which consists
of estimators at different layers where the predictions of estimators from current layer are …

… We apply five tree-based basic ensemble learning classifiers during the first step of stacking
learning to construct five base classifiers, including a bagging-based classifier (RF) [28] and …

… We adopt a stacked ensemble learning method, which has a two-layer structure and is easy
… stacked ensemble learning method is shown in Figure 2. We construct a two-layer stacked …

… ensemble-based learning approach to optimize image classification performance. In addition,
we integrate the proposed ensemble learning … , the proposed ensemble learning method …

… In this regard, we proposed a stacking learning method for therapeutic peptide recognition
called PreTPStack. The major contribution of PreTP-Stack is as follows: (i) According to the …

… of choosing stacking against blending ensemble methods in … stacking ensemble learning
was crucial to our empirical study. We upgraded this system to support the blending ensemble …