TY  - BOOK
AU  - Juneja,Hursh
AU  - Huynh,Ngoc Phien
AU  - Sadananda,Ramakoti
AU  - Nagarur,Nagendra N.
ED  - The Government Of Norway, 
TI  - The back-propagation scheme in data classification: software and empirical guidelines
T2  - Thesis
PY  - 1992///
CY  - Bangkok
PB  - Asian Institute of Technology
KW  - Neural networks (Computer science)
KW  - Information storage and retrieval systems
N1  - A thesis submitted in partial fulfillment of the requirement for the degree of Master of  Engineering, School of Engineering and Technology; Thesis (M.Eng.) - Asian Institute of Technology, 1992
N2  - The present study explores the applicability of Neural Networks to the problem of  classification which is of great importance in many areas. For this purpose, a common neural  network with back propagation aigorithm was used. First of all, a fully menu-driven and user  friendly software package was developed to facilitate the application of this type of networks. It  caters to numerical data input and is a fas~ high precision tool for neural network training.  From a careful comparative study, it was found that for both normal and non-normal data,  neural networks can result in better classification accuracy as comp{u00A5}ed to classical statistical  methods, the latter being based on the assumption of an underlying data distribution. An attempt  has also been made to formulate some guieielines to answer the questions regarding selection of  a suitable learning rate and changing of thi ~ rate for faster convergence while training without any  modifications to the training software. A third guideline has been proposed to decide the extent  of training itself. All these can be achieved by careful examination of error and actual output  curves of the training
UR  - http://203.159.5.9/ait-thesis/detail.php?q=B16613
ER  -