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Создание тестовых данных для систем контроля и мониторинга рынка, содержащих встроенные алгоритмы машинного обучения

https://doi.org/10.15514/ISPRAS-2017-29(4)-18

Полный текст:

Об авторах

О. Москалёва
Exactpro, LSEG
Россия


А. Громова
Exactpro, LSEG
Россия


Список литературы

1. FCA (financial conduct authority) (online). Доступно по ссылке: https://handbook.fca.org.uk/

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8. Ou Y., Cao L., Luo C., Liu L.:Mining Exceptional Activity Patterns in Microstructure Data. In Proc. of International Conference on Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM, 2008, pp. 884-887

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10. Murphy C., Kaiser G., Arias M.: An Approach to Software Testing of Machine Learning Applications. Proc of the 19th International Conference on Software Engineering and Knowledge Engineering (SEKE), Boston MA, Jul 2007, pp. 167-172

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12. Murphy C., Kaiser G., Arias M.: Parameterizing Random Test Data According to Equivalence Classes. Proc of the 2nd International Workshop on Random Testing (RT'07), Atlanta GA, Nov 2007, pp. 38-41

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14. Murphy C., Kaiser G., Hu L., Wu L.: Properties of Machine Learning Applications for Use in Metamorphic Testing. Proc of the 20th International Conference on Software Engineering and Knowledge Engineering (SEKE), Redwood City CA, Jul 2008, pp. 867-872.

15. Zhang J., Wang Z., Zhang L., Hao D., Zang L., Cheng S., Zhang Lu.: Predictive Mutation Testing. In Proc. of ISSTA’16, Saarbrücken, Germany, July 18-20, 2016, pp. 342-353


Рецензия

Для цитирования:


Москалёва О., Громова А. Создание тестовых данных для систем контроля и мониторинга рынка, содержащих встроенные алгоритмы машинного обучения. Труды Института системного программирования РАН. 2017;29(4):269-282. https://doi.org/10.15514/ISPRAS-2017-29(4)-18

For citation:


Moskaleva O., Gromova A. Creating Test Data for Market Surveillance Systems with Embedded Machine Learning Algorithms. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2017;29(4):269-282. https://doi.org/10.15514/ISPRAS-2017-29(4)-18



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ISSN 2079-8156 (Print)
ISSN 2220-6426 (Online)