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1. FeatTS FeatTS Public

   FeatTS is a Semi-Supervised Clustering method that leverages features extracted from the raw time series to create clusters that reflect the original time series.

   Python 17 1

2. TimeSeriesSeedingKMeans TimeSeriesSeedingKMeans Public

   In this repository I've implemented the Semi Supervised Time Series Clustering called Seeded kMeans using the DTW as distance.

   Python 2 1

3. softlab-unimore/time2feat softlab-unimore/time2feat Public

   Time2Feat: Learning Interpretable Representations for Multivariate Time Series Clustering

   Python 20 5

4. softlab-unimore/bert-attention-for-em softlab-unimore/bert-attention-for-em Public

   Python 9 4

5. boniolp/kGraph boniolp/kGraph Public

   Graph Embedding for Interpretable Time Series Clustering

   Python 10

6. softlab-unimore/t2fweb softlab-unimore/t2fweb Public

   Python