Feature extraction is the practice of enhancing machine learning by finding characteristics in the data that help solve a particular problem. For time series data, feature extraction can be performed using various time series analysis and decomposition techniques.
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Time-series data have core components like seasonality, trend, and cycles . For example, ice-cream sales usually have yearly seasonality — you can reasonably predict the next summer’s sales based on this year’s. Similarly, temperatures or air quality measurements have daily seasonality or also, yearly.21 Tem 2021
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