Title :
Effects of data complexity on the intelligent diagnostic reasoning
Author :
Marzi, Arash ; Marzi, Hosein
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Ottawa, Ottawa, ON, Canada
fDate :
May 31 2015-June 4 2015
Abstract :
The objective was to train several Artificial Neural Networks (ANNs) with different training functions in order to gain an understanding of the effect of dataset complexity on performance. The utilization of varying training functions permitted ANN diversity; and allowing for enhanced diagnostic reasoning in classification. This improvement is achieved by expediting training stage, calibrating classification. The proposed technique is applied to a number of dataset to verify performance improvements. Particular application of the proposed technique is demonstrated by applying methodology for medical diagnostics.
Keywords :
inference mechanisms; medical diagnostic computing; neural nets; pattern classification; ANN; artificial neural network; classification; data complexity; dataset complexity; intelligent diagnostic reasoning; medical diagnostics; training function; Artificial intelligence; Artificial neural networks; Breast cancer; Classification algorithms; Diseases; Medical diagnostic imaging; Training; Classification; Diagnostics; Neural Networks;
Conference_Titel :
Humanitarian Technology Conference (IHTC2015), 2015 IEEE Canada International
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4799-8961-4
DOI :
10.1109/IHTC.2015.7238069
