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Subspace Clustering Visualization

Subspace Clustering Visualization. What is Subspace Clustering?. Why SC Visualization?. Richer output … but more complex Existing traditional clustering vis don’t work well Very few existing solutions for the problem. Unsorted. Sorted Dimensions. Sorted Dimensions and Clusters.

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Subspace Clustering Visualization

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  1. Subspace ClusteringVisualization

  2. What is Subspace Clustering?

  3. Why SC Visualization? • Richer output … but more complex • Existing traditional clustering vis don’t work well • Very few existing solutions for the problem

  4. Unsorted Sorted Dimensions Sorted Dimensions and Clusters

  5. Unsorted Sorted Dimensions Sorted Dimensions and Clusters

  6. Research Issues • Supporting Parameterization • Dealing with Cluster Stability • Steering the Algorithm

  7. TRADITIONAL PROCESS e.g., K & D Params Data Clustering Results

  8. SOLUTION 1: Results Comparison No Guessing Params Result 1 Data Clustering Result 2 . . . Result N • Issues: • parameter space can be huge! • vis for comparison not well researched • parameter sensitivity

  9. SOLUTION 2: Opening the Box Params Data Clustering Partial Result • Issues: • requires expert knowledge • requires lengthy procedures • is it realistic? • does it outperform the machine?

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