… diversity of ensemble members … ensemble learning techniques. Experimental results in a
wide variety of natural domains suggest that these multistrategy ensemble learning techniques …

… we survey the various ensemble learning techniques that is prevalent in machine learning.
… Section VI, analysis the Mixture of experts, an important study in ensemble learning and we …

… There are two main approaches to designing ensemble learning algorithms. … this technique
improves the performance of both decision-tree and backpropagation learning algorithms on …

… This note presents a chronological review of the literature on ensemble learning which has
accumulated over the past twenty years. The idea of ensemble learning is to employ multiple …

… of ensemble learning, and we also give an extra introduction for the combination … ensemble
learning with other machine learning hot spots such as deep learning, reinforcement learning…

… Ensemble learning techniques have achieved state-of-the-art performance in diverse machine
learning … overview of ensemble learning, covering the three main ensemble methods: …

… of ensemble learning, explain how ensemble learning work and present its advantages. The
next section presents different general approaches for building an ensemble … an ensemble …

… can be broadly defined as a machine learning system that is constructed with a set of …
introduce core of ensemble learning and key techniques to improve ensemble learning. Based on …

… (1) We used four heterogeneous ensemble-learning techniques for LSM by combining deep
learning methods and conventional machine learning methods. Specifically, we chose CNN …

… could outperform every other machine learning algorithm under all … ensemble learning
technique has been developed in response to this claim [16,17]. Ensemble learning techniques …