@INPROCEEDINGS { Rsds3812,
author = {Jelonek, Jacek and Krawiec, Krzysztof and Slowinski, Roman and Szymas, Janusz}, 
title = {Rough Set Reduction of Features for Picture-Based Reasoning}, 
booktitle = {Soft Computing}, 
conference = {International Workshop on Rough Sets and Soft Computing}, 
pages = {89--92}, 
publisher = {The Society for Computer Simulation}, 
address = {San Diego, U.S.A.}, 
month = {November}, 
year = 1994, 
editor = {Lin, Tsau Young and Wildberger, A.M.}, 
isbn = {1-56555-077-3}, 
abstract = {The study concerns the classification of the histological pictures and constitutes a typical example of picture - based reasoning. The task is to distinguish different types of tumours of the central nervous system. First, some features are extracted from the image. The set of pictorial attributes is then reduced, using the concepts of reduct, core and quickly of classification coming from the rough set theory (Pawlak 1993). Afterwards, the reduced set of features constitutes the input data for particular classifiers: the layered neural network with backpropagation algorithm and potential-function method. Several tests have been performed to compare these methods and to explore the influence of rough-set reduction on the final quality of classification.}, 
keywords = {image processing and recognition, machine learning, classification, }, 
}