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  • 1.
    Havås Klug, Sebastian
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Comparison of machine learning models for hardware configuration dimensioning tool2020Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis we answer the following questions.Is machine learning a viable replacement for Ericsson’s CPU dimensioning tool CANDI? How do di↵erent learners perform on the problem at hand? How to fairly and accurately asses the performance of di↵erent learners?A framework for training, optimizing and evaluating Scikit-learn compatible estimators and a application for predicting EPG on SSR CPU usage are created.

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