Adaptive Learning for Service Monitoring Data

• URL: http://arxiv.org/abs/2208.12281v1
• Date: Thu, 25 Aug 2022 18:06:45 GMT
• Title: Adaptive Learning for Service Monitoring Data
• Authors: Farzana Anowar, Samira Sadaoui, Hardik Dalal
• Abstract summary: This study develops an adaptive classification approach using Learn++ that can handle evolving data distributions. We employ consecutive data chunks obtained from an industrial application to evaluate the performance of the predictors incrementally.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Service monitoring applications continuously produce data to monitor their availability. Hence, it is critical to classify incoming data in real-time and accurately. For this purpose, our study develops an adaptive classification approach using Learn++ that can handle evolving data distributions. This approach sequentially predicts and updates the monitoring model with new data, gradually forgets past knowledge and identifies sudden concept drift. We employ consecutive data chunks obtained from an industrial application to evaluate the performance of the predictors incrementally.

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