Short review of dimensionality reduction methods for failure detection

Agnieszka Pocha,

Krzysztof Misztal,

Paweł Morkisz


Size of the data is often a challenge in real-life applications. Especially when working with time series data, when next sample is produced every few milliseconds and can include measurement from hundreds of sensors, one has to take the dimensionality of the data into consideration. In this work, we compare various dimensionality reduction methods for time series data and check their performance on failure detection task. We work on sensory data coming from existing machines.

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