Analysis of a two-stage Bayes classifiers construction method: The 2-dimensional case
| Autor: | Juris Sinica-Sinavskis, Aivars Lorencs |
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| Rok vydání: | 2013 |
| Předmět: |
Pseudorandom number generator
business.industry Computer science Pattern recognition Statistical model Bayes classifier Machine learning computer.software_genre Bayes' theorem Naive Bayes classifier Construction method Control and Systems Engineering Signal Processing Bayes error rate Stage (hydrology) Artificial intelligence business computer Software |
| Zdroj: | Automatic Control and Computer Sciences. 47:254-266 |
| ISSN: | 1558-108X 0146-4116 |
| DOI: | 10.3103/s0146411613050040 |
| Popis: | The paper discusses the properties of a two-stage Bayes classifier construction method in a case when the objects are represented with two quantitative features. The aim of the study was to show that, in general, the two-stage approach allows one to enhance the precision of the classification results. The main method of the investigation is statistical modeling while applying a pseudorandom number generator. In some cases, the statistical modeling results are compared with the results of theoretical inferences. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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