can describeand drawthreedifferent typesof clustersAsked afollow upquestionto aquestioncan givea reasonfor usingclusteringanalysisAsked aquestion thatconfusedeverybodyAsked aquestion thepresenterdidn't knowthe answer toSaid helloto onlinestudentsAnswered aquestion thepresenteraskedINCORRECTLYcan draw thedifferencebetweenhierarchical &partitionalclusteringknowsdifferencebetweencomplete andpartialclusteringfinds amistake inthe slideAsked aquestion thepresenterdidn't knowthe answer toAnswered aquestion thepresenteraskedCORRECTLYdidn't checkemail duringentirepresentationcan describethe ideabehind K-meansclusteringReadingmaterialshaveannotationsand highlightsBrought thereadingmaterialsto classclapped atthe end ofpresentationGave ausefulexample toexplain aconceptdidn'tfallasleep!participatedin at leastonediscussionknows how tochoose thenumber ofclusters in K-meansclusteringCan namethree basicclusteringalgorithmsdidn't usephone duringentirepresentationcan statedifference betweenexclusive,overlapping, andfuzzy clusteringcan describeand drawthreedifferent typesof clustersAsked afollow upquestionto aquestioncan givea reasonfor usingclusteringanalysisAsked aquestion thatconfusedeverybodyAsked aquestion thepresenterdidn't knowthe answer toSaid helloto onlinestudentsAnswered aquestion thepresenteraskedINCORRECTLYcan draw thedifferencebetweenhierarchical &partitionalclusteringknowsdifferencebetweencomplete andpartialclusteringfinds amistake inthe slideAsked aquestion thepresenterdidn't knowthe answer toAnswered aquestion thepresenteraskedCORRECTLYdidn't checkemail duringentirepresentationcan describethe ideabehind K-meansclusteringReadingmaterialshaveannotationsand highlightsBrought thereadingmaterialsto classclapped atthe end ofpresentationGave ausefulexample toexplain aconceptdidn'tfallasleep!participatedin at leastonediscussionknows how tochoose thenumber ofclusters in K-meansclusteringCan namethree basicclusteringalgorithmsdidn't usephone duringentirepresentationcan statedifference betweenexclusive,overlapping, andfuzzy clustering

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