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MiniRocket

Data Skeptic

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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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