Speaker
Scott Israel
(Boston University)
Description
Using a gradient boosted decision tree, we can improve momentum track quality selection on the mu2e tracker simulation data. Using a decision tree rather than an artificial neural network halves the training time and classification time. Eventually this machine learning model will be used in production to analyze real data.
Primary author
Scott Israel
(Boston University)
Co-author
Andrew Edmonds
(Boston University)