@inproceedings{d02d85de1d3c4395bc41c5cba7506cab,
title = "Feature selection and learning curves of a multilayer perceptron chromosome classifier",
abstract = "A multilayer perceptron (MLP) neural network (NN) was used for human chromosome classification. The significance of relevant chromosome features to the classification procedure was evaluated using a feature selection mechanism. It yielded the benefit of using only a part of the available features to get performance close to the ultimate one, classifying chromosomes of 5 types. Only 10-20 examples were required for the MLP NN classifier to reach its supreme performance disregarding the number of features used. Furthermore, the empirical entropie error of the classifier was found to be highly comparable to the 1/t function that is a universal learning curve.",
author = "B. Lemer and H. Guterman and I. Dinstein and Y. Romern",
note = "Publisher Copyright: {\textcopyright} 1994 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.; 12th IAPR International Conference on Pattern Recognition - Conference B: Pattern Recognition and Neural Networks, ICPR 1994 ; Conference date: 09-10-1994 Through 13-10-1994",
year = "1994",
month = jan,
day = "1",
language = "English",
series = "Proceedings - International Conference on Pattern Recognition",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "497--499",
booktitle = "Proceedings of the 12th IAPR International Conference on Pattern Recognition - Conference B",
address = "United States",
}