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CodeSignal

Hierarchical Clustering Deep Dive

via CodeSignal

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Overview

Unpack the complexity of hierarchical clustering, learning to construct and interpret dendrograms for valuable data insights, and apply your knowledge to real-world data.

Syllabus

  • Unit 1: Hierarchical Clustering in R
    • Agglomerative Clustering on Iris Dataset
    • Agglomerative Clustering of Iris Dataset
    • Adjust Agglomerative Clustering to Three Clusters
    • Euclidean Distance Computation in Clustering
    • Implement Hierarchical Clustering with R's hclust
  • Unit 2: Distance Metrics in Clustering
    • Agglomerative Clustering Using Cosine Distance
    • Modifying Distance Metric in Agglomerative Clustering
    • Modify Code to Implement Cosine Distance in Clustering Task
    • Implementing Distance Measures for Clustering
    • Hierarchical Clustering with R
  • Unit 3: Linkage Methods in Clustering
    • Planetary System Clustering Using Hierarchical Methods
    • Experimenting with Complete Linkage in Hierarchical Clustering
    • Exploring Clustering with Ward.D2 Linkage and Euclidean Distance
    • Clustering Stars with Average Linkage Method
  • Unit 4: Dendrograms in Hierarchical Clustering
    • Hierarchical Clustering of Cities Based on Coordinates
    • Modify Clustering Method to Average Linkage
    • Visualizing Hierarchical Clustering with Dendrogram
    • Clustering and Visualizing Fictional City Coordinates

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