This paper examines several clustering techniques to minimize training data size while keeping the associated performance models accurate. Our results indicate ...
In this paper, we examine the feasibility and the possible benefit of reducing the size of collaboratively shared training data for performance models of data ...
Training Data Reduction for Performance Models of Data ...
www.researchgate.net › publication › 35...
This paper examines several clustering techniques to minimize training data size while keeping the associated performance models accurate. Our results indicate ...
This paper examines several clustering techniques to minimize training data size while keeping the associated performance models accurate. Our results indicate ...
This paper examines several clustering techniques to minimize training data size while keeping the associated performance models accurate, and indicates ...
Training Data Reduction for Performance Models of Data ...
www.researchgate.net › publication › 35...
This paper examines several clustering techniques to minimize training data size while keeping the associated performance models accurate. Our results indicate ...
Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud. J Will, O Arslan, J Bader, D Scheinert, L Thamsen. 2021 IEEE International ...
May 26, 2023 · AI won't eliminate data analytics, at most it will just result in employers seeking more conceptually sound candidates. As is, you can't ...
This study explores the use of deep learning, specifically autoencoders, for data reduction in the edge-cloud IoT data analytics context. Autoencoders are ...
Apr 23, 2022 · The results show that using the approach, the number of samples for training could be reduced by more than 99 % , while also increasing the ...