Abstract
Approaches to automatically generate useful features from sensory data are introduced in this chapter. Most of the approaches introduced focus on datasets that have a temporal ordering. Features in the time domain are explained, thereby summarizing both numerical and categorical values in a certain historical window. The frequency domain is also discussed, including Fourier transformations and features one can derive from these transformations. In addition, the extraction of features from unstructured data is discussed, mainly focusing on text data.
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Hoogendoorn, M., Funk, B. (2018). Feature Engineering Based on Sensory Data. In: Machine Learning for the Quantified Self. Cognitive Systems Monographs, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-319-66308-1_4
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DOI: https://doi.org/10.1007/978-3-319-66308-1_4
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-66307-4
Online ISBN: 978-3-319-66308-1
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