Towards Autonomous Machine Reasoning: Multi- Stage Classification System with Intermediate Learning

Stolar, M, Lech, M, Bolia, R and Skinner, M 2017, 'Towards Autonomous Machine Reasoning: Multi- Stage Classification System with Intermediate Learning', in Tadeusz A Wysocki & Beata J Wysocki (ed.) Proceedings of the 11th International Conference on Signal Processing and Communication Systems (ICSPCS 2017), Queensland, Australia, 13-15 December 2017, pp. 29-34.


Document type: Conference Paper
Collection: Conference Papers

Title Towards Autonomous Machine Reasoning: Multi- Stage Classification System with Intermediate Learning
Author(s) Stolar, M
Lech, M
Bolia, R
Skinner, M
Year 2017
Conference name ICSPCS 2017
Conference location Queensland, Australia
Conference dates 13-15 December 2017
Proceedings title Proceedings of the 11th International Conference on Signal Processing and Communication Systems (ICSPCS 2017)
Editor(s) Tadeusz A Wysocki & Beata J Wysocki
Publisher IEEE
Place of publication United States
Start page 29
End page 34
Total pages 6
Abstract This paper describes a new concept of multi-stage classification with intermediate learning (MSIL), and validates a simple two-stage version of the MSIL on nine popular test datasets. The first stage performs classical learning and inference based on features calculated directly from the data. The second stage learns and infers the final diagnosis using diagnostic labels generated at the first stage. Since both stages are trained independently, the learning results of the second stage do not alter the learning results accomplished at the first stage. This important property enables the generation of more complex, multi-channel and/or multi-level machine reasoning systems consisting of algebraically connected basic two-stage units. Classification tests showed that in almost all tested cases, the accuracy achieved at the first stage was further improved by the second stage of classification. This means that primary learning from the data can be improved by secondary learning from mistakes made when classifying the data parameters.
Subjects Signal Processing
Keyword(s) Speech
Cognition
Databases
Task analysis
Recurrent neural networks
Matlab
DOI - identifier 10.1109/ICSPCS.2017.8270486
Copyright notice © 2017 IEEE
ISBN 9781538628874
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