FAQ
Download
1 / 13

FAQ - PowerPoint PPT Presentation


  • 149 Views
  • Uploaded on

FAQ. Olli Virmajoki. UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND. 11.12.2004. Merge Cost Equation. s i = i th cluster of data vertors s ij = cluster formed by merging i th and j th clusters n i = number of data vectors in s i

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' FAQ' - tia


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
FAQ

Olli Virmajoki

UNIVERSITY OF JOENSUU

DEPARTMENT OF COMPUTER SCIENCE

JOENSUU, FINLAND

11.12.2004


Merge cost equation
Merge Cost Equation

  • si = i th cluster of data vertors

  • sij = cluster formed by merging i th and j th clusters

  • ni = number of data vectors in si

  • nij = numberof data vectors in sij

  • = centroid (mean) of the data vectors in si

  • = centroid (mean) of the data vectors in sij

  • = average squared error between and the data vectors in si

  • = average squared error between and the data vectors in sij

  • = inner product of x and y








Exact calculation of the removal cost
Exact calculation of the removal cost

  • Data vectors xi in the cluster sa are divided into subclusters sa,j

  • Removal is conseptually three step process: (1) remove the vectors from the current cluster sa (2) form the subclusters sa,j (3) merge the subclusters to the neighbor clusters sj


Removal cost
Removal cost

  • The first term is the cost of the cluster before removal

  • The second term is the sum of the cost values inside the subclusters

  • The third term is the sum of the costs of merging the subclusters sa,jto their neighbor clusters sj



Number of clusterings
Number of clusterings

  • M N iterations to cover the search space

  • N distinct vertors to M non-distinct codewords lowers the search by M !

  • Clusterings(N,M)


Number of clusterings1
Number of clusterings

  • Consider a number of vectors ordered into groups, one vector at a time

  • Each vector in turn may:

    • Either form a new group on its own, or

    • Combine with other vectors already in a formed group.


ad