Like "time_series_features_extractor"， although the current overlap parameter can solve the issue, it requires calculating specific values, which can be cumbersome. If we had a parameter similar to "step", along with window_size, it would be much easier to implement a sliding window effect. For example, with [1, 2, 3, 4, 5], window_size=3, and step=2, we could achieve [1, 2, 3] and [3, 4, 5]. This is quite common in time series data, whereas calculating the overlap ratio can be more complicated."
Like "time_series_features_extractor"， although the current overlap parameter can solve the issue, it requires calculating specific values, which can be cumbersome. If we had a parameter similar to "step", along with window_size, it would be much easier to implement a sliding window effect. For example, with [1, 2, 3, 4, 5], window_size=3, and step=2, we could achieve [1, 2, 3] and [3, 4, 5]. This is quite common in time series data, whereas calculating the overlap ratio can be more complicated."