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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:

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data-reactid=\"8006\"></div></div></div></div><footer class=\"footer-container\" role=\"contentinfo\" data-reactid=\"8007\"><div class=\"ui container\" data-reactid=\"8008\"><div class=\"ui two column stackable grid\" data-reactid=\"8009\"><div class=\"row\" style=\"padding-top:0px;padding-bottom:0px;\" data-reactid=\"8010\"><div class=\"seven wide column\" data-reactid=\"8011\"><div class=\"foot"], "copyright__copyright__copyright": ["jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by 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Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct 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the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide.", "jects in the subset by the mean.\n      \u2022 The super-instance also carries a weight, which is the number of objects it represents\n    \u2022 Conduct modified k-means clustering to respect cannot-link constraints\n      \u2022 Modify the center-assignment process in k-means to a nearest feasible center assignment\n      \u2022 An object is assigned to the nearest center so that the assignment respects all cannot-link constraints\n\nSpeaker notes:\n\nContent Tools\n\nSources\n\nThere are currently no sources for this slide."]}