Machine Learning with IceCube Data(pdf)
The prompt atmospheric muon flux is not yet measured. Proving its existence is challenging because it is only possible to measure the sum of the conventional and prompt flux. To get a significant excess in the spectrum, high statistics and a good handle of the systematic uncertainties is necessary. A data mining approach to select these high energetic muons from IceCube data will be shown. This presentation will give a brief overview of supervised machine learning algorithms which are used.