Said helloto onlinestudentsknowsdifferencebetweencomplete andpartialclusteringfinds amistake inthe slideknows how tochoose thenumber ofclusters in K-meansclusteringcan givea reasonfor usingclusteringanalysiscan statedifference betweenexclusive,overlapping, andfuzzy clusteringAsked aquestion thepresenterdidn't knowthe answer todidn'tfallasleep!can describethe ideabehind K-meansclusteringcan describeand drawthreedifferent typesof clustersReadingmaterialshaveannotationsand highlightsdidn't checkemail duringentirepresentationclapped atthe end ofpresentationcan draw thedifferencebetweenhierarchical &partitionalclusteringAnswered aquestion thepresenteraskedCORRECTLYAsked aquestion thatconfusedeverybodyBrought thereadingmaterialsto classdidn't usephone duringentirepresentationAnswered aquestion thepresenteraskedINCORRECTLYAsked afollow upquestionto aquestionCan namethree basicclusteringalgorithmsAsked aquestion thepresenterdidn't knowthe answer toparticipatedin at leastonediscussionGave ausefulexample toexplain aconceptSaid helloto onlinestudentsknowsdifferencebetweencomplete andpartialclusteringfinds amistake inthe slideknows how tochoose thenumber ofclusters in K-meansclusteringcan givea reasonfor usingclusteringanalysiscan statedifference betweenexclusive,overlapping, andfuzzy clusteringAsked aquestion thepresenterdidn't knowthe answer todidn'tfallasleep!can describethe ideabehind K-meansclusteringcan describeand drawthreedifferent typesof clustersReadingmaterialshaveannotationsand highlightsdidn't checkemail duringentirepresentationclapped atthe end ofpresentationcan draw thedifferencebetweenhierarchical &partitionalclusteringAnswered aquestion thepresenteraskedCORRECTLYAsked aquestion thatconfusedeverybodyBrought thereadingmaterialsto classdidn't usephone duringentirepresentationAnswered aquestion thepresenteraskedINCORRECTLYAsked afollow upquestionto aquestionCan namethree basicclusteringalgorithmsAsked aquestion thepresenterdidn't knowthe answer toparticipatedin at leastonediscussionGave ausefulexample toexplain aconcept

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