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mcfly: deep learning for time series

Authors: van Kuppevelt, Dafne; Meijer, Christiaan; Huber, Florian; van Hees, Vincent; Solino Fernandez, Breixo; Bos, Patrick; Spaaks, Jurriaan; +5 Authors

mcfly: deep learning for time series

Abstract

The goal of mcfly is to ease the use of deep learning technology for time series classification. The advantage of deep learning is that it can handle raw data directly, without the need to compute signal features. Deep learning does not require expert domain knowledge about the data, and has been shown to be competitive with conventional machine learning techniques. As an example, you can apply mcfly on accelerometer data for activity classification.

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Keywords

machine learning, deep learning, time series, automated machine learning

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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