Title :
Input selection in learning systems: A brief review of some important issues and recent developments
Author :
Hu, Chenglin ; Wan, Feng
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Macau, Macau, China
Abstract :
Input selection is a crucial step for learning systems especially when in system modeling and identification the dataset is with a large number of variables, as a redundant input usually impairs the transparency of the underlying model and also increases the complexity of computation. The primary objective of input selection is to select the relevant inputs under the available information. This paper gives a brief review of some important issues and recent developments in the literature.
Keywords :
computational complexity; learning (artificial intelligence); computational complexity; input selection; learning systems; Data visualization; Filters; Fuzzy systems; Input variables; Learning systems; Modeling; Neural networks; Nonlinear distortion; Principal component analysis; Sampling methods;
Conference_Titel :
Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
Conference_Location :
Jeju Island
Print_ISBN :
978-1-4244-3596-8
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2009.5277050