can givea reasonfor usingclusteringanalysisdidn'tfallasleep!Asked aquestion thatconfusedeverybodydidn't usephone duringentirepresentationAsked aquestion thepresenterdidn't knowthe answer toknows how tochoose thenumber ofclusters in K-meansclusteringclapped atthe end ofpresentationAsked afollow upquestionto aquestionSaid helloto onlinestudentscan statedifference betweenexclusive,overlapping, andfuzzy clusteringGave ausefulexample toexplain aconceptfinds amistake inthe slidedidn't checkemail duringentirepresentationknowsdifferencebetweencomplete andpartialclusteringAsked aquestion thepresenterdidn't knowthe answer toparticipatedin at leastonediscussionReadingmaterialshaveannotationsand highlightscan draw thedifferencebetweenhierarchical &partitionalclusteringcan describethe ideabehind K-meansclusteringAnswered aquestion thepresenteraskedCORRECTLYBrought thereadingmaterialsto classcan describeand drawthreedifferent typesof clustersAnswered aquestion thepresenteraskedINCORRECTLYCan namethree basicclusteringalgorithmscan givea reasonfor usingclusteringanalysisdidn'tfallasleep!Asked aquestion thatconfusedeverybodydidn't usephone duringentirepresentationAsked aquestion thepresenterdidn't knowthe answer toknows how tochoose thenumber ofclusters in K-meansclusteringclapped atthe end ofpresentationAsked afollow upquestionto aquestionSaid helloto onlinestudentscan statedifference betweenexclusive,overlapping, andfuzzy clusteringGave ausefulexample toexplain aconceptfinds amistake inthe slidedidn't checkemail duringentirepresentationknowsdifferencebetweencomplete andpartialclusteringAsked aquestion thepresenterdidn't knowthe answer toparticipatedin at leastonediscussionReadingmaterialshaveannotationsand highlightscan draw thedifferencebetweenhierarchical &partitionalclusteringcan describethe ideabehind K-meansclusteringAnswered aquestion thepresenteraskedCORRECTLYBrought thereadingmaterialsto classcan describeand drawthreedifferent typesof clustersAnswered aquestion thepresenteraskedINCORRECTLYCan namethree basicclusteringalgorithms

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