H Rajadurai, UD Gandhi - Neural computing and applications, 2022 - Springer
… In this paper, we propose stackedensemblelearning model for network intrusion detection by using gradient boosting machine (GBM) and random forest (RF) algorithms. The proposed …
… Thus, this study evaluates an ensemblelearning model that combines bagging and stacking methods applied to … 3 illustrates the stackingensemblelearning workflow used in this paper. …
… of stackingensemblelearning 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 stackedensemblelearning technique which consists of estimators at different layers where the predictions of estimators from current layer are …
F Li, J Chen, Z Ge, Y Wen, Y Yue… - Briefings in …, 2021 - academic.oup.com
… We apply five tree-based basic ensemblelearning classifiers during the first step of stacking learning to construct five base classifiers, including a bagging-based classifier (RF) [28] and …
… We adopt a stackedensemblelearning method, which has a two-layer structure and is easy … stackedensemblelearning 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 ensemblelearning … , the proposed ensemblelearning method …
K Yan, H Lv, J Wen, Y Guo, Y Xu… - IEEE/ACM transactions …, 2022 - ieeexplore.ieee.org
… In this regard, we proposed a stackinglearning 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 … stackingensemblelearning was crucial to our empirical study. We upgraded this system to support the blending ensemble …