A Python Framework for Exhaustive Machine Learning Algorithms and Features Evaluations

@article{Dubosson2016APF,
  title={A Python Framework for Exhaustive Machine Learning Algorithms and Features Evaluations},
  author={Fabien Dubosson and Stefano Bromuri and Michael Ignaz Schumacher},
  journal={2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)},
  year={2016},
  pages={987-993}
}
Machine learning domain has grown quickly the last few years, in particular in the mobile eHealth domain. In the context of the DINAMO project, we aimed to detect hypoglycemia on Type 1 diabetes patients by using their ECG, recorded with a sport-like chest belt. In order to know if the data contain enough information for this classification task, we needed to apply and evaluate machine learning algorithms on several kinds of features. We have built a Python toolbox for this reason. It is built… CONTINUE READING

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