Feature engineering based on sensory data

Mark Hoogendoorn*, Burkhardt Funk

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

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.

Original languageEnglish
Title of host publicationMachine Learning for the Quantified Self
Subtitle of host publicationOn the Art of Learning from Sensory Data
PublisherSpringer/Verlag
Chapter4
Pages51-70
Number of pages20
ISBN (Electronic)9783319663081
ISBN (Print)9783319663074
DOIs
Publication statusE-pub ahead of print - 27 Sep 2017

Publication series

NameCognitive Systems Monographs
Volume35
ISSN (Print)1867-4925
ISSN (Electronic)1867-4933

Cite this