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.
|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|
|Number of pages||6|
|Publication status||Published - 1995|
- n-tuple recognition
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.