participatedin at leastonediscussiondidn't checkemail duringentirepresentationcan statedifference betweenexclusive,overlapping, andfuzzy clusteringknows how tochoose thenumber ofclusters in K-meansclusteringAsked afollow upquestionto aquestioncan draw thedifferencebetweenhierarchical &partitionalclusteringclapped atthe end ofpresentationBrought thereadingmaterialsto classAnswered aquestion thepresenteraskedCORRECTLYfinds amistake inthe slidecan givea reasonfor usingclusteringanalysisdidn't usephone duringentirepresentationAsked aquestion thepresenterdidn't knowthe answer toknowsdifferencebetweencomplete andpartialclusteringAsked aquestion thatconfusedeverybodyGave ausefulexample toexplain aconceptcan describeand drawthreedifferent typesof clustersReadingmaterialshaveannotationsand highlightsAnswered aquestion thepresenteraskedINCORRECTLYdidn'tfallasleep!Asked aquestion thepresenterdidn't knowthe answer toSaid helloto onlinestudentsCan namethree basicclusteringalgorithmscan describethe ideabehind K-meansclusteringparticipatedin at leastonediscussiondidn't checkemail duringentirepresentationcan statedifference betweenexclusive,overlapping, andfuzzy clusteringknows how tochoose thenumber ofclusters in K-meansclusteringAsked afollow upquestionto aquestioncan draw thedifferencebetweenhierarchical &partitionalclusteringclapped atthe end ofpresentationBrought thereadingmaterialsto classAnswered aquestion thepresenteraskedCORRECTLYfinds amistake inthe slidecan givea reasonfor usingclusteringanalysisdidn't usephone duringentirepresentationAsked aquestion thepresenterdidn't knowthe answer toknowsdifferencebetweencomplete andpartialclusteringAsked aquestion thatconfusedeverybodyGave ausefulexample toexplain aconceptcan describeand drawthreedifferent typesof clustersReadingmaterialshaveannotationsand highlightsAnswered aquestion thepresenteraskedINCORRECTLYdidn'tfallasleep!Asked aquestion thepresenterdidn't knowthe answer toSaid helloto onlinestudentsCan namethree basicclusteringalgorithmscan describethe ideabehind K-meansclustering

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