finds amistake inthe slidecan statedifference betweenexclusive,overlapping, andfuzzy clusteringknows how tochoose thenumber ofclusters in K-meansclusteringAsked afollow upquestionto aquestionparticipatedin at leastonediscussiondidn'tfallasleep!Answered aquestion thepresenteraskedINCORRECTLYcan draw thedifferencebetweenhierarchical &partitionalclusteringclapped atthe end ofpresentationcan describethe ideabehind K-meansclusteringAsked aquestion thepresenterdidn't knowthe answer toCan namethree basicclusteringalgorithmsAsked aquestion thepresenterdidn't knowthe answer toGave ausefulexample toexplain aconceptcan describeand drawthreedifferent typesof clustersdidn't usephone duringentirepresentationBrought thereadingmaterialsto classAnswered aquestion thepresenteraskedCORRECTLYdidn't checkemail duringentirepresentationReadingmaterialshaveannotationsand highlightsknowsdifferencebetweencomplete andpartialclusteringAsked aquestion thatconfusedeverybodySaid helloto onlinestudentscan givea reasonfor usingclusteringanalysisfinds amistake inthe slidecan statedifference betweenexclusive,overlapping, andfuzzy clusteringknows how tochoose thenumber ofclusters in K-meansclusteringAsked afollow upquestionto aquestionparticipatedin at leastonediscussiondidn'tfallasleep!Answered aquestion thepresenteraskedINCORRECTLYcan draw thedifferencebetweenhierarchical &partitionalclusteringclapped atthe end ofpresentationcan describethe ideabehind K-meansclusteringAsked aquestion thepresenterdidn't knowthe answer toCan namethree basicclusteringalgorithmsAsked aquestion thepresenterdidn't knowthe answer toGave ausefulexample toexplain aconceptcan describeand drawthreedifferent typesof clustersdidn't usephone duringentirepresentationBrought thereadingmaterialsto classAnswered aquestion thepresenteraskedCORRECTLYdidn't checkemail duringentirepresentationReadingmaterialshaveannotationsand highlightsknowsdifferencebetweencomplete andpartialclusteringAsked aquestion thatconfusedeverybodySaid helloto onlinestudentscan 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. finds a mistake in the slide
  2. can state difference between exclusive, overlapping, and fuzzy clustering
  3. knows how to choose the number of clusters in K-means clustering
  4. Asked a follow up question to a question
  5. participated in at least one discussion
  6. didn't fall asleep!
  7. Answered a question the presenter asked INCORRECTLY
  8. can draw the difference between hierarchical & partitional clustering
  9. clapped at the end of presentation
  10. can describe the idea behind K-means clustering
  11. Asked a question the presenter didn't know the answer to
  12. Can name three basic clustering algorithms
  13. Asked a question the presenter didn't know the answer to
  14. Gave a useful example to explain a concept
  15. can describe and draw three different types of clusters
  16. didn't use phone during entire presentation
  17. Brought the reading materials to class
  18. Answered a question the presenter asked CORRECTLY
  19. didn't check email during entire presentation
  20. Reading materials have annotations and highlights
  21. knows difference between complete and partial clustering
  22. Asked a question that confused everybody
  23. Said hello to online students
  24. can give a reason for using clustering analysis