DocumentCode
1652919
Title
The Least Covering Algorithm
Author
Shu, Zhao ; Yanping, Zhang ; Ling, Zhang ; Feng, Xu
Author_Institution
Anhui Univ., Hefei
fYear
2007
Firstpage
181
Lastpage
185
Abstract
Learning system in machine learning is conducted to confirm the description of specific concept, according to a set of samples and background knowledge that teachers offer. In the point of epistemology , when study the samples, we always focus on the sample set, so nothing can be fabricated, in other words, if we only have a few samples, we can get limited knowledge after learning them, then it is impossible to distinguish every unknown situation. To get the principle which is close to the sample as much as possible, this paper puts forward the least covering principle of machine learning, which is the aim of the covering algorithm of multi-layered feedforward neural network; it also makes a study of the properties of least covering, then brings forward a geometry algorithm to get the least covering that is based on this; at last it gives the solving process of least covering using the programming method.
Keywords
feedforward neural nets; geometry; learning (artificial intelligence); epistemology; geometry algorithm; learning system; least covering algorithm; machine learning; multilayered feedforward neural network; sample set; Bismuth; Laboratories; Learning systems; Machine learning; Machine learning algorithms; Multi-layer neural network; Neural networks; Niobium; Security; Signal processing algorithms; covering algorithm; least covering; quadratic programming;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference, 2007. CCC 2007. Chinese
Conference_Location
Hunan
Print_ISBN
978-7-81124-055-9
Electronic_ISBN
978-7-900719-22-5
Type
conf
DOI
10.1109/CHICC.2006.4347407
Filename
4347407
Link To Document