Data Science, Machine Learning

Highly Comparative Time Series Analysis — a paper review

Analysis of time series feature extraction for comparison, clustering, classification, and annotation

In machine learning with time series, using features extracted from series is more powerful than simply treating a time series in a tabular form, with each date/timestamp in a separate column. Such features can capture the characteristics of series, such as trend and autocorrelations.