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IEEE/ICACT20260142 Slide.19        [Big Slide]	Oral Presentation
	Besides unsupervised methods, we also apply supervised learning to train profiles of our services. For example, build a model to predict CPU/ Disk IO consumption of a service in normal operation and use for detect possible bugs in software or configuration after a software update. We use regression algorithms and used in conjunction with a threshold for the difference between predicted and actual values.

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