Current Slide

Small screen detected. You are viewing the mobile version of SlideWiki. If you wish to edit slides you will need to use a larger device.

Constraint-Based Clustering Methods (I):Handling Hard Constraints

  • Handling hard constraints: Strictly respect the constraints in cluster assignments
  • Example: The COP-k-means algorithm
    • Generate super-instances for must-link constraints
      • Compute the transitive closure of the must-link constraints
      • To represent such a subset, replace all those objects in the subset by the mean.
      • The super-instance also carries a weight, which is the number of objects it represents
    • Conduct modified k-means clustering to respect cannot-link constraints
      • Modify the center-assignment process in k-means to a nearest feasible center assignment
      • An object is assigned to the nearest center so that the assignment respects all cannot-link constraints

Speaker notes:

Content Tools


There are currently no sources for this slide.