Abstract
The n-tuple recognition method was tested on 11 large real-world data sets and its performance compared to 23 other classification algorithms. On 7 of these, the results show no systematic performance gap between the n-tuple method and the others. Evidence was found to support a possible explanation for why the n-tuple method yields poor results for certain datasets. Preliminary empirical results of a study of the confidence interval (the difference between the two highest scores) are also reported. These suggest a counter-intuitive correlation between the confidence interval distribution and the overall classification performance of the system.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Second Weightless Neural Network Workshop 1995, Computing with Logical Neurons |
| Editors | D. L. Bisset |
| Place of Publication | Canterbury |
| Publisher | University of Kent |
| Pages | 29-34 |
| Number of pages | 6 |
| Publication status | Published - 1995 |
Keywords
- n-tuple recognition
- algorithms
- datasets
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Rohwer, R., & Morciniec, M. (1995). Benchmarking the n-tuple classifier with statlog dataset. In D. L. Bisset (Ed.), Proceedings of the Second Weightless Neural Network Workshop 1995, Computing with Logical Neurons (pp. 29-34). University of Kent.