Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/12715
ชื่อเรื่อง: Performance Prediction of Jupyter Notebook in JupyterHub using Machine Learning
ผู้แต่ง: Prathanrat P.
Polprasert C.
Keywords: Artificial intelligence
Decision trees
Forecasting
Average delay
Jupyter Notebook
JupyterHub
Machine learning models
Mean absolute error
Mean absolute percentage error
Performance prediction
Random forest modeling
Learning systems
วันที่เผยแพร่: 2018
บทคัดย่อ: In this paper, we employ machine learning to predict the performance of Jupyter notebook on JupyterHub. We show that the notebook's CPU profile, the notebook's RAM profile, number of users and average delay between cells are crucial features that impact the performance of the machine learning models to accurately predict the performance of Jupyter notebook in term of the response time. We characterize the performance of our model to predict the notebook's response time in terms of the mean absolute error (MAE) and mean absolute percentage error (MAPE). Results show that the random forest model yields strongest performance to predict the performance of Jupyter notebook with MAPE equal to 9.849% and MAE equal to 13.768 seconds. with r-square equal to 0.93. © 2018 IEEE.
URI: https://ir.swu.ac.th/jspui/handle/123456789/12715
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060037072&doi=10.1109%2fICIIBMS.2018.8550030&partnerID=40&md5=8fdf63797476d9d48b4b3d813543a032
Appears in Collections:Scopus 1983-2021

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