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1. 1. Detecting Performance Anomalies in a Mobile Application with Unsupervised Machine Learning

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Lukas Saari; [2019]
   Keywords : ;

   Abstract : Unsupervised anomaly detection algorithms are applied with the purpose of identifying performance regressions in a mobile application. To evaluate the performance, a labeled artificial data set is generated that is based on a real data set and that aims to reflect its properties. READ MORE