machine learning for outlier identification

[martin-raden]

preprocessing for ATP project (idea by Bela in Nov. 2017):

problem: data from HF measurement often contains outliers and artefact profiles, which have to be removed before generating a consensus with MICA.

solution: machine learning based identification of hf outliers based on manual curated data (pos/neg training/testing data available)