… This work has proposed an ensemble approach using the concept of stacking for effective
network intrusion detection. Two heterogeneous datasets like UNSW NB-15 (emulated) and …

… field have typically focused on generating the ensemble … In contrast, Stacking generates the
members of the Stacking ensemble … Given a dataset S, Stacking first generates randomly a …

… To evaluate the performance of the proposed stacking ensemble based framework on
the dataset consisting of multiple sentiment class labels, we have used the Twitter Emotion …

… We compare these models in terms of their datasets, ensemble structure, selection … bagging
+ stacking (bstacking) framework to fuse the predictions of heterogeneous ensemble models…

… We suggest a two-level stacking heterogeneous ensemble algorithm combining RF, …
stacking-based ensemble model. According to the analysis results, the two-level stacking ensemble …

… using the stacking method to realize the ensemble of the P-DCNNs, we first use the TL idea
to fine-tune the weights of the P-DCNNs on the divided space target ISAR image data set to …

… ensemble model by combining the SMOTE technique with the heterogeneous stacking
ensemble to get the most benefit and performance in training a dataset that focus on the minority …

… and investigates the Stacking Multi-Learning Ensemble (SMLE… a flexible ensemble framework
in light of blend heterogeneous … For this dataset, we accordingly developed homogeneous …

… , a multistage heterogeneous stacking ensemble model was … The proposed multistage
heterogeneous stacking ensemble … considering this value was the structure of our dataset. The …

… This paper proposes to use stacked ensemble to deal with the class imbalance and enhance
… for imbalanced datasets. Some researchers contributed methods for unbalanced datasets, …