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2min chapter
MiniRocket
Data Skeptic
A Brief Introduction to Time Series Approaches
Rocket is a method where we take our input time series and transform them using a large number of random convolutional kernels. We then use the transformed features to train a simple linear classifier. It turns out that this process, although it seems very simple, produces high classification accuracy and is quite fast and able.
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