I am trying to perform a time-series classification using features. This means that the feature extraction algorithm calculates characteristics such as the average or maximal value of the time series and use it for classification.
However, my time-series is small have about 10 data points each.
e.g., [10, 10, 10, 10, 8, 5, 3, 2, 1, 1], [8, 8, 8, 8, 9, 5, 4, 3, 2, 1], and so on.
In that case what are the features I can extract?
I came accross a really cool python package named as tsfresh that calculates a huge number of time-series features. However, since my time-series is small I am worried if that is suitable for me.
I am happy to provide more details if needed.