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  • LLMs context (llms.txt)
  • Getting Started
  • User Guide
  • Reference
  • Community
  • GitHub
  • LLMs context (llms.txt)

Section Navigation

  • Examples Gallery
    • Data Containers
      • The Three Types of Sequences
      • Trajectories
    • Visualisation
      • Timeline
      • Barplot
      • Spanplot
      • Distribution
    • Temporal Alignment (Zeroing)
      • Sequence Level Zeroing
      • Trajectory-Level Zeroing
    • Criteria
      • EntityCriterion
      • StaticCriterion
      • TimeCriterion
      • PatternCriterion
      • LengthCriterion
      • RankCriterion
    • Entity Metrics
      • Entity Metric: Hamming Distance
      • Custom Entity Metric
    • Sequence Metrics
      • Sequence Metrics: LinearPairwise
      • Sequence Metrics: Edit Distance
      • Sequence Metrics: LCP
      • Sequence Metrics: LCS
      • Sequence Metrics: DTW
      • Sequence Metrics: SoftDTW
      • Sequence Metrics: Chi²
      • Custom Sequence Metric
    • Trajectory Metrics
      • Trajectory Metrics: Aggregation Trajectory Metric
      • Custom Trajectory Metric
    • Clustering
      • Clustering: Hierarchical Clustering
      • Clustering: Partitioning Around Medoids (PAM)
      • Clustering: CLARA (Clustering LARge Applications)
  • Tutorials
    • Building pools from multiple sources
    • MIMIC-IV: Clinical Cohort Analysis
      • Exploring a patient cohort
      • Filtering and preparing a cohort
      • Analysing and clustering cohort sequences
      • Survival analysis from cohort clusters
      • Learning clinical temporal patterns with SWoTTeD
    • MOOC: Learning Session Analysis
      • Exploring learner activity sequences
      • Clustering learning sessions by action patterns
    • Time Series to Sequences
      • Discretizing time series into sequences
  • User Guide
  • Examples Gallery
  • Clustering

Clustering#

Clustering partitions sequences into groups based on pairwise distances between sequences or trajectories.

Clustering: Hierarchical Clustering

Clustering: Hierarchical Clustering

Clustering: Partitioning Around Medoids (PAM)

Clustering: Partitioning Around Medoids (PAM)

Clustering: CLARA (Clustering LARge Applications)

Clustering: CLARA (Clustering LARge Applications)

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Custom Trajectory Metric

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Clustering: Hierarchical Clustering

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