can describethe ideabehind K-meansclusteringdidn't checkemail duringentirepresentationAsked afollow upquestionto aquestionknows how tochoose thenumber ofclusters in K-meansclusteringAnswered aquestion thepresenteraskedINCORRECTLYdidn't usephone duringentirepresentationReadingmaterialshaveannotationsand highlightscan describeand drawthreedifferent typesof clustersBrought thereadingmaterialsto classknowsdifferencebetweencomplete andpartialclusteringGave ausefulexample toexplain aconceptSaid helloto onlinestudentsclapped atthe end ofpresentationAnswered aquestion thepresenteraskedCORRECTLYAsked aquestion thepresenterdidn't knowthe answer tofinds amistake inthe slidedidn'tfallasleep!can statedifference betweenexclusive,overlapping, andfuzzy clusteringAsked aquestion thatconfusedeverybodyparticipatedin at leastonediscussioncan givea reasonfor usingclusteringanalysiscan draw thedifferencebetweenhierarchical &partitionalclusteringCan namethree basicclusteringalgorithmsAsked aquestion thepresenterdidn't knowthe answer tocan describethe ideabehind K-meansclusteringdidn't checkemail duringentirepresentationAsked afollow upquestionto aquestionknows how tochoose thenumber ofclusters in K-meansclusteringAnswered aquestion thepresenteraskedINCORRECTLYdidn't usephone duringentirepresentationReadingmaterialshaveannotationsand highlightscan describeand drawthreedifferent typesof clustersBrought thereadingmaterialsto classknowsdifferencebetweencomplete andpartialclusteringGave ausefulexample toexplain aconceptSaid helloto onlinestudentsclapped atthe end ofpresentationAnswered aquestion thepresenteraskedCORRECTLYAsked aquestion thepresenterdidn't knowthe answer tofinds amistake inthe slidedidn'tfallasleep!can statedifference betweenexclusive,overlapping, andfuzzy clusteringAsked aquestion thatconfusedeverybodyparticipatedin at leastonediscussioncan givea reasonfor usingclusteringanalysiscan draw thedifferencebetweenhierarchical &partitionalclusteringCan namethree basicclusteringalgorithmsAsked aquestion thepresenterdidn't knowthe answer to

Clustering and Community Detection - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. can describe the idea behind K-means clustering
  2. didn't check email during entire presentation
  3. Asked a follow up question to a question
  4. knows how to choose the number of clusters in K-means clustering
  5. Answered a question the presenter asked INCORRECTLY
  6. didn't use phone during entire presentation
  7. Reading materials have annotations and highlights
  8. can describe and draw three different types of clusters
  9. Brought the reading materials to class
  10. knows difference between complete and partial clustering
  11. Gave a useful example to explain a concept
  12. Said hello to online students
  13. clapped at the end of presentation
  14. Answered a question the presenter asked CORRECTLY
  15. Asked a question the presenter didn't know the answer to
  16. finds a mistake in the slide
  17. didn't fall asleep!
  18. can state difference between exclusive, overlapping, and fuzzy clustering
  19. Asked a question that confused everybody
  20. participated in at least one discussion
  21. can give a reason for using clustering analysis
  22. can draw the difference between hierarchical & partitional clustering
  23. Can name three basic clustering algorithms
  24. Asked a question the presenter didn't know the answer to