Yiqi Deng
ABSTRACT
Real world machine learning, where data is sampled continuously, may in theory be classifiable into distinct and unchanging categories but in practice the classification becomes non-trivial because the nature of the background noise continuously changes. Applying distinct and unchanging categories for data ignores the fact that for some applications where the categories of data may remain constant, the background noise constantly changes, and thus the ability for a supervised learning method to work is limited. In this work, we propose a novel method based on an Artificial Immune System (AIS) and implemented on a systemic computer, which is designed to adapt itself over continuous arrival of data to cope with changing patterns of noise without requirement for feedback, as a result of its own experience.
- Choi, Samjin, and Zhongwei Jiang. Comparison of envelope extraction algorithms for cardiac sound signal segmentation. Expert Systems with Applications 34.2 (2008): 1056--1069. Google Scholar
Digital Library
- Bentley, Peter J. Systemic computation: A model of interacting systems with natural characteristics. The International Journal of Parallel, Emergent and Distributed Systems 22.2 (2007): 103--121. Google ScholarDigital Library
- Le Martelot, Erwan, Peter J. Bentley, and R. Beau Lotto. Eating data is good for your immune system: an artificial metabolism for data clustering using systemic computation. Artificial Immune Systems. Springer Berlin Heidelberg, 2008. 412--423. Google ScholarDigital Library
- Bentley, P. and Nordehn, G. and Coimbra, M. and Mannor, S.(2011). The Pascal Classifying Heart Sounds Challenge. http://www.peterjbentley.com/heartchallenge/index.htmlGoogle Scholar
- Das, S., Matthews, B. L., Srivastava, A. N., & Oza, N. C. (2010, July). Multiple kernel learning for heterogeneous anomaly detection: algorithm and aviation safety case study. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 47--56). ACM. Google ScholarDigital Library
Index Terms
- Adapting to dynamically changing noise during learning of heart sounds: an AIS-based approach using systemic computation
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