date accessioned | 2020-03-12T21:07:30Z | |
date available | 2020-03-12T21:07:30Z | |
date issued | 2014 | |
identifier other | 6925708.pdf | |
identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/1037814?locale-attribute=en&show=full | |
format | general | |
language | English | |
publisher | IEEE | |
title | Executive Roundtable | |
type | Conference Paper | |
contenttype | Metadata Only | |
identifier padid | 8164221 | |
subject keywords | data reduction | |
subject keywords | feedforward neural nets | |
subject keywords | learning (artificial intelligence) | |
subject keywords | pattern classification | |
subject keywords | vectors | |
subject keywords | UCI machine learning repository | |
subject keywords | data classification | |
subject keywords | feedforward neural network | |
subject keywords | four-class synthetic problem | |
subject keywords | input vectors | |
subject keywords | minimum boundary vector distance selection | |
subject keywords | paired vector | |
subject keywords | reduced training set | |
subject keywords | training set reduction algorithm | |
subject keywords | Accuracy | |
subject keywords | Biological neural networks | |
subject keywords | Equations | |
subject keywords | Shape | |
subject keywords | Support vector machines | |
subject keywords | Training | |
subject keywords | Vectors | |
subject keywords | boundary detection | |
subject keywords | data reduction | |
subject keywords | neural netwo | |
identifier doi | 10.1109/InfoSEEE.2014.6948071 | |
journal title | igh-Performance Interconnects (HOTI), 2014 IEEE 22nd Annual Symposium on | |
filesize | 76674 | |
citations | 0 | |