Self-Organizing Maps for High Dimensional Feature Space Problems

ISBN-13: 9783659885280 / Angielski / Miękka / 2016 / 172 str.

Alaa Sagheer

Opis

Self Organizing Map SOM is one of the wide spread neural network approaches which enable feature extraction, visualization in pattern recognition and data mining problems. However, two major problems have been observed when SOM is used in high dimensional feature space problems: the recognition rate is dropped when unseen data are used, and expensive computational cost when using large data sets. In this book, we develop new hierarchical search algorithm for SOM. Several experiments are conducted for some pattern recognition applications showed the superiority of the proposed SOM over traditional SOM and other related approaches.

O autorze

Alaa Sagheer received his Ph.D. in Intelligent Systems from Faculty of Engineering, Kyushu University, Japan in 2007. He is an Associate Professor at Aswan University, Egypt. Since 2014, Sagheer joined Department of Computer Science at King Faisal University, Saudi Arabia. He is a senior member at IEEE. Research interests are Machine Learning, AI.