didn'tfallasleep!Asked afollow upquestionto aquestioncan statedifference betweenexclusive,overlapping, andfuzzy clusteringBrought thereadingmaterialsto classAsked aquestion thatconfusedeverybodycan draw thedifferencebetweenhierarchical &partitionalclusteringdidn't usephone duringentirepresentationSaid helloto onlinestudentscan describethe ideabehind K-meansclusteringclapped atthe end ofpresentationcan describeand drawthreedifferent typesof clustersReadingmaterialshaveannotationsand highlightsknows how tochoose thenumber ofclusters in K-meansclusteringAsked aquestion thepresenterdidn't knowthe answer toAsked aquestion thepresenterdidn't knowthe answer toCan namethree basicclusteringalgorithmsparticipatedin at leastonediscussionAnswered aquestion thepresenteraskedCORRECTLYfinds amistake inthe slideAnswered aquestion thepresenteraskedINCORRECTLYGave ausefulexample toexplain aconceptdidn't checkemail duringentirepresentationknowsdifferencebetweencomplete andpartialclusteringcan givea reasonfor usingclusteringanalysisdidn'tfallasleep!Asked afollow upquestionto aquestioncan statedifference betweenexclusive,overlapping, andfuzzy clusteringBrought thereadingmaterialsto classAsked aquestion thatconfusedeverybodycan draw thedifferencebetweenhierarchical &partitionalclusteringdidn't usephone duringentirepresentationSaid helloto onlinestudentscan describethe ideabehind K-meansclusteringclapped atthe end ofpresentationcan describeand drawthreedifferent typesof clustersReadingmaterialshaveannotationsand highlightsknows how tochoose thenumber ofclusters in K-meansclusteringAsked aquestion thepresenterdidn't knowthe answer toAsked aquestion thepresenterdidn't knowthe answer toCan namethree basicclusteringalgorithmsparticipatedin at leastonediscussionAnswered aquestion thepresenteraskedCORRECTLYfinds amistake inthe slideAnswered aquestion thepresenteraskedINCORRECTLYGave ausefulexample toexplain aconceptdidn't checkemail duringentirepresentationknowsdifferencebetweencomplete andpartialclusteringcan givea reasonfor usingclusteringanalysis

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