How do you cluster time series?
hardAnswer
- (1) Feature extraction: extract statistics (mean, variance, autocorrelation, FFT bands) and cluster the feature vectors.
- (2) Dynamic Time Warping (DTW) distance + k-medoids / hierarchical.
- (3) Shape-based: k-Shape (normalized cross-correlation).
- (4) Embed with sequence autoencoder / TS2Vec then cluster embeddings.
- Rule: DTW for shape similarity, feature-based for interpretability, embedding-based for large heterogeneous series.
Check yourself — multiple choice
- Naive Euclidean
- Feature extraction / DTW + k-medoids / k-Shape / embedding then cluster; DTW for shape, features for interpretability, embeddings for scale
- Same as k-means
- Random
Time-series clustering: features / DTW / k-Shape / embeddings depending on scale.
#clustering#applications
Practise Unsupervised Learning
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