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About 10 1016@j Inffus 2013 04 006
This document provides a survey of multiple classifier systems (MCS) from the perspective of hybrid intelligent systems. MCS combine several classifier systems that can be built using the same or different models and datasets. This allows MCS to fuse classification decisions at different levels, overcoming limitations of single classifiers. The document discusses major MCS issues like diversity, decision fusion methods, and applications. It reviews the history of MCS and highlights their advantages like improved performance over individual classifiers when data is scarce or abundant. MCS are seen as a promising approach and active area of research in pattern recognition.
Detailed Information
| Author: | ['Zakaria Sutomo'] |
|---|---|
| Publication Year: | 2016 |
| Pages: | 31 |
| Language: | English |
| Format: | |
| Price: | FREE |
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