Why Raw Vectorization Is the Right Choice for Ultra-Short Time Series (T ≤ 10)
This report analyzes why standard vectorization methods — statistical summary (mean/var/AUC), automatic feature extraction (tsfresh, catch22), convolutional representations (MiniRocket), and self-supervised embeddings (TS2Vec) — fail when the time series length T is very short, especially T ≤ 10. As an alternative, it argues that Raw Vectorization (Identity Mapping) is not just an easy fallback but…
