Can namethree basicclusteringalgorithmscan describethe ideabehind K-meansclusteringAsked aquestion thatconfusedeverybodyknowsdifferencebetweencomplete andpartialclusteringfinds amistake inthe slideReadingmaterialshaveannotationsand highlightscan statedifference betweenexclusive,overlapping, andfuzzy clusteringdidn'tfallasleep!can givea reasonfor usingclusteringanalysisAsked aquestion thepresenterdidn't knowthe answer toAnswered aquestion thepresenteraskedCORRECTLYBrought thereadingmaterialsto classAsked afollow upquestionto aquestionparticipatedin at leastonediscussionclapped atthe end ofpresentationcan draw thedifferencebetweenhierarchical &partitionalclusteringAnswered aquestion thepresenteraskedINCORRECTLYknows how tochoose thenumber ofclusters in K-meansclusteringAsked aquestion thepresenterdidn't knowthe answer toSaid helloto onlinestudentsdidn't checkemail duringentirepresentationdidn't usephone duringentirepresentationGave ausefulexample toexplain aconceptcan describeand drawthreedifferent typesof clustersCan namethree basicclusteringalgorithmscan describethe ideabehind K-meansclusteringAsked aquestion thatconfusedeverybodyknowsdifferencebetweencomplete andpartialclusteringfinds amistake inthe slideReadingmaterialshaveannotationsand highlightscan statedifference betweenexclusive,overlapping, andfuzzy clusteringdidn'tfallasleep!can givea reasonfor usingclusteringanalysisAsked aquestion thepresenterdidn't knowthe answer toAnswered aquestion thepresenteraskedCORRECTLYBrought thereadingmaterialsto classAsked afollow upquestionto aquestionparticipatedin at leastonediscussionclapped atthe end ofpresentationcan draw thedifferencebetweenhierarchical &partitionalclusteringAnswered aquestion thepresenteraskedINCORRECTLYknows how tochoose thenumber ofclusters in K-meansclusteringAsked aquestion thepresenterdidn't knowthe answer toSaid helloto onlinestudentsdidn't checkemail duringentirepresentationdidn't usephone duringentirepresentationGave ausefulexample toexplain aconceptcan 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. can describe the idea behind K-means clustering
  3. Asked a question that confused everybody
  4. knows difference between complete and partial clustering
  5. finds a mistake in the slide
  6. Reading materials have annotations and highlights
  7. can state difference between exclusive, overlapping, and fuzzy clustering
  8. didn't fall asleep!
  9. can give a reason for using clustering analysis
  10. Asked a question the presenter didn't know the answer to
  11. Answered a question the presenter asked CORRECTLY
  12. Brought the reading materials to class
  13. Asked a follow up question to a question
  14. participated in at least one discussion
  15. clapped at the end of presentation
  16. can draw the difference between hierarchical & partitional clustering
  17. Answered a question the presenter asked INCORRECTLY
  18. knows how to choose the number of clusters in K-means clustering
  19. Asked a question the presenter didn't know the answer to
  20. Said hello to online students
  21. didn't check email during entire presentation
  22. didn't use phone during entire presentation
  23. Gave a useful example to explain a concept
  24. can describe and draw three different types of clusters