Artificial intelligence (AI) is a scientific discipline that aims to create intelligent machines.
Machine learning is a popular and practical AI subfield that aims to automatically improve …

Ensemble methods that train multiple learners and then combine them for use, with Boosting
and Bagging as representatives, are a kind of state-of-theart learning approach. It is well …

Ensemble learning is an imperative study in the domain of machine learning. Over the
previous years, ensemble learning has drawn considerable attention in the field of artificial …

Researchers from various disciplines such as pattern recognition, statistics, and machine
learning have explored the use of ensemble methodology since the late seventies. Thus …

Ensemble learning is fast becoming a popular choice for machine learning models in the
data science world. Ensemble methods combine the output of machine learning models in …

Ensemble classifier refers to a group of individual classifiers that are cooperatively trained
on data set in a supervised classification problem. In this paper we present a review of …

Ensembles of learning machines constitute one of the main current directions in machine
learning research, and have been applied to a wide range of real problems. Despite of the …

Ensemble methods are considered the state‐of‐the art solution for many machine learning
challenges. Such methods improve the predictive performance of a single model by training …

" Learning" describes many different activities ranging from CONCEPT LEARNING (qv) to
REINFORCEMENT LEARNING (qv). The best-understood form of statistical learning is …

Ensemble learning is a powerful machine learning paradigm which has exhibited apparent
advantages in many applications. An ensemble in the context of machine learning can be …