Distributed and parallel time series feature extraction for industrial big data applications

25 Oct 2016Maximilian ChristAndreas W. Kempa-LiehrMichael Feindt

The all-relevant problem of feature selection is the identification of all strongly and weakly relevant attributes. This problem is especially hard to solve for time series classification and regression in industrial applications such as predictive maintenance or production line optimization, for which each label or regression target is associated with several time series and meta-information simultaneously... (read more)

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