… The data set was obtained from the UCI machine learning benchmark repository. It is
available by anonymous ftp at ics.uci.edu (128.195.1.1) in directory /pub/machine-learning-…

… of machine learning methods are developed to address ordinal regression problems (or
redesigned from nominal classification domains). These methods include perceptron learning [7]…

… recent classification ensemble methods briefly. Since the role of diversity of an ensemble
was recognized [4] [5], a few NCL methods and their … AdaBoost and Classification Ensembles …

… limit the practical application of NC method for ensemble learning. … called negative correlation
learning via correlation-corrected data (NCCD). It differs from all previous NC methods that …

… ensemble learning approach by negative correlation learning (NCL) [21, 22, 23]. NCL is an
… This chapter investigates a specific ensemble learning approach by negative correlation …

… This paper will focus on this kind of ensemble learning algorithm… methods on single learners.
In this paper, we extend the Bayesian inference from a single learner to ensemble methods …

… We propose a novel ensemble framework, named global negative correlation learning (GNCL), …
In summary, the goal of this article is to propose a new framework for ensemble learning …

… Secondly, the ensemble learning is also investigated in this research. … In this research,
a new ensemble transfer learning by using negative correlation ensemble is proposed. …

… Ensemble learning has been proven to be theoretically and empirically superior to single
models by state-of-the-art literature as a method of combining pre-trained models in a certain …

… of learners that work together as a committee, has attracted a lot of research interest in the
machine learning … Most ensemble learning algorithms train the individual neural network …