### Abstract

Construction methods for multi-valued classification (multi-class) systems using binary classifiers are discussed and evaluated by a trade-off model for system evaluation based on rate-distortion theory. Suppose the multi-class systems consisted of M(≥3) categories and N(≥M-1) binary classifiers, then they can be represented by a matrix W, where the matrix W is given by a table of M code words with length N, called a code word table. For a document classification task, the relationship between the probability of classification error P_{e} and the number of binary classifiers N for given M is investigated, and we show that our constructed systems satisfy desirable properties such as “Flexible”, and “Elastic”. In particular, modified Reed Muller codes perform well: they are shown to be “Effective elastic”. As a second application we consider a hand-written character recognition task, and we show that the desirable properties are also satisfied.

Original language | English |
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Title of host publication | Trends and Advances in Information Systems and Technologies |

Publisher | Springer-Verlag |

Pages | 909-919 |

Number of pages | 11 |

ISBN (Print) | 9783319777115 |

DOIs | |

Publication status | Published - 2018 Jan 1 |

Event | 6th World Conference on Information Systems and Technologies, WorldCIST 2018 - Naples, Italy Duration: 2018 Mar 27 → 2018 Mar 29 |

### Publication series

Name | Advances in Intelligent Systems and Computing |
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Volume | 746 |

ISSN (Print) | 2194-5357 |

### Other

Other | 6th World Conference on Information Systems and Technologies, WorldCIST 2018 |
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Country | Italy |

City | Naples |

Period | 18/3/27 → 18/3/29 |

### Fingerprint

### Keywords

- Binary classifier
- ECOC
- Error correcting codes
- Exhaustive code
- Multi-valued classification
- Trade-off model

### ASJC Scopus subject areas

- Control and Systems Engineering
- Computer Science(all)

### Cite this

*Trends and Advances in Information Systems and Technologies*(pp. 909-919). (Advances in Intelligent Systems and Computing; Vol. 746). Springer-Verlag. https://doi.org/10.1007/978-3-319-77712-2_86