Title :
A Dynamic Integrated Model in Machine Learning and Its Application
Author :
Wang Huan ; Zhou Ke ; Wu Ruofan
Author_Institution :
Eng. Training Center, Univ. of Sci. & Technol. Beijing, Beijing, China
Abstract :
In the past decades, machine learning has got great progress. The technique of machine learning is widely used in many areas, such as banking and scientific research. Different from traditional research directions, a dynamic integration is getting more important, which could offer an improvement and optimize the learning efficiency with the known models and algorithms. This paper is aimed to offer a dynamic integrated model on which many models and algorithms could be dynamic integrated. Three dimensions are used to describe the knowledge space. Through the superimposing of the learning clouds, which are used to describe the state of study in one area, we describe the progress of learning. Another discrete model is offered as a simplification of the model, and it also works as a platform for simulation.
Keywords :
learning (artificial intelligence); cloud learning; dynamic integrated model; dynamic integration; learning efficiency; machine learning; Algorithm design and analysis; Computational modeling; Data mining; Heuristic algorithms; Machine learning; Machine learning algorithms; Training; Discrete Model; Dynamic Integrated Model; Machine Learning;
Conference_Titel :
Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9247-3
DOI :
10.1109/GCIS.2010.111