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- W2981451208 abstract "Machine Learning (ML) has shown its capability to analyse, classify, and make predictions based on large data sets. Network performance analysis and evaluation focuses on finding and expressing qualitative, quantitative and formal relationships between performance-related parameters, with specific interest in asymptotic behaviours. This work introduces the notion of performance analytics as performance modeling with help of ML. In particular, it demonstrates the applicablibility of the ML algorithm M5P to such performance analytics, as the parameters of the generated model trees allow for identifying approximations together the applicable parameter sub-spaces in a straightforward approach. We present a set of examples with focus on post-analysis of analytically obtained performance results for asymptotic behaviour." @default.
- W2981451208 created "2019-11-01" @default.
- W2981451208 creator A5051117813 @default.
- W2981451208 date "2019-08-01" @default.
- W2981451208 modified "2023-10-14" @default.
- W2981451208 title "Performance Analytics by Means of the M5P Machine Learning Algorithm" @default.
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- W2981451208 doi "https://doi.org/10.1109/itc31.2019.00023" @default.
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