Towards interactive Machine Learning (iML): Applying Ant Colony Algorithms to Solve the Traveling Salesman Problem with the Human-in-the-Loop Approach

@inproceedings{Holzinger2016TowardsIM,
  title={Towards interactive Machine Learning (iML): Applying Ant Colony Algorithms to Solve the Traveling Salesman Problem with the Human-in-the-Loop Approach},
  author={Andreas Holzinger and Markus Plass and Katharina Holzinger and Gloria Cerasela Crisan and Camelia-Mihaela Pintea and Vasile Palade},
  booktitle={CD-ARES},
  year={2016}
}
Most Machine Learning (ML) researchers focus on automatic Machine Learning (aML) where great advances have been made, for example, in speech recognition, recommender systems, or autonomous vehicles. Automatic approaches greatly benefit from the availability of “big data”. However, sometimes, for example in health informatics, we are confronted not a small number of data sets or rare events, and with complex problems where aML-approaches fail or deliver unsatisfactory results. Here, interactive… CONTINUE READING
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