Can namethree basicclusteringalgorithmsdidn'tfallasleep!finds amistake inthe slideAsked aquestion thepresenterdidn't knowthe answer toSaid helloto onlinestudentsclapped atthe end ofpresentationAsked afollow upquestionto aquestionknows how tochoose thenumber ofclusters in K-meansclusteringdidn't usephone duringentirepresentationcan statedifference betweenexclusive,overlapping, andfuzzy clusteringAnswered aquestion thepresenteraskedINCORRECTLYparticipatedin at leastonediscussioncan draw thedifferencebetweenhierarchical &partitionalclusteringGave ausefulexample toexplain aconceptknowsdifferencebetweencomplete andpartialclusteringcan describethe ideabehind K-meansclusteringcan givea reasonfor usingclusteringanalysisAsked aquestion thatconfusedeverybodyAnswered aquestion thepresenteraskedCORRECTLYAsked aquestion thepresenterdidn't knowthe answer todidn't checkemail duringentirepresentationBrought thereadingmaterialsto classReadingmaterialshaveannotationsand highlightscan describeand drawthreedifferent typesof clustersCan namethree basicclusteringalgorithmsdidn'tfallasleep!finds amistake inthe slideAsked aquestion thepresenterdidn't knowthe answer toSaid helloto onlinestudentsclapped atthe end ofpresentationAsked afollow upquestionto aquestionknows how tochoose thenumber ofclusters in K-meansclusteringdidn't usephone duringentirepresentationcan statedifference betweenexclusive,overlapping, andfuzzy clusteringAnswered aquestion thepresenteraskedINCORRECTLYparticipatedin at leastonediscussioncan draw thedifferencebetweenhierarchical &partitionalclusteringGave ausefulexample toexplain aconceptknowsdifferencebetweencomplete andpartialclusteringcan describethe ideabehind K-meansclusteringcan givea reasonfor usingclusteringanalysisAsked aquestion thatconfusedeverybodyAnswered aquestion thepresenteraskedCORRECTLYAsked aquestion thepresenterdidn't knowthe answer todidn't checkemail duringentirepresentationBrought thereadingmaterialsto classReadingmaterialshaveannotationsand highlightscan describeand drawthreedifferent typesof clusters

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