Feature Selection for Learning to Predict Outcomes of Compute Cluster Jobs with Application to Decision Support

no code implementations • 14 Dec 2020 • Adedolapo Okanlawon, Huichen Yang, Avishek Bose, William Hsu, Dan Andresen, Mohammed Tanash

We present a supervised learning model trained on a Simple Linux Utility for Resource Management (Slurm) data set of HPC jobs using three different techniques for selecting features: linear regression, lasso, and ridge regression.

feature selection Management +1

Machine Learning for Predictive Analytics of Compute Cluster Jobs

no code implementations • 20 May 2018 • Dan Andresen, William Hsu, Huichen Yang, Adedolapo Okanlawon

We address the problem of predicting whether sufficient memory and CPU resources have been requested for jobs at submission time.

BIG-bench Machine Learning General Classification