Said helloto onlinestudentsBrought thereadingmaterialsto classcan statedifference betweenexclusive,overlapping, andfuzzy clusteringcan describethe ideabehind K-meansclusteringReadingmaterialshaveannotationsand highlightsAsked aquestion thatconfusedeverybodyGave ausefulexample toexplain aconceptAsked afollow upquestionto aquestionAsked aquestion thepresenterdidn't knowthe answer tocan draw thedifferencebetweenhierarchical &partitionalclusteringcan describeand drawthreedifferent typesof clustersparticipatedin at leastonediscussionAnswered aquestion thepresenteraskedINCORRECTLYAnswered aquestion thepresenteraskedCORRECTLYdidn'tfallasleep!clapped atthe end ofpresentationfinds amistake inthe slideAsked aquestion thepresenterdidn't knowthe answer todidn't usephone duringentirepresentationcan givea reasonfor usingclusteringanalysisknows how tochoose thenumber ofclusters in K-meansclusteringdidn't checkemail duringentirepresentationCan namethree basicclusteringalgorithmsknowsdifferencebetweencomplete andpartialclusteringSaid helloto onlinestudentsBrought thereadingmaterialsto classcan statedifference betweenexclusive,overlapping, andfuzzy clusteringcan describethe ideabehind K-meansclusteringReadingmaterialshaveannotationsand highlightsAsked aquestion thatconfusedeverybodyGave ausefulexample toexplain aconceptAsked afollow upquestionto aquestionAsked aquestion thepresenterdidn't knowthe answer tocan draw thedifferencebetweenhierarchical &partitionalclusteringcan describeand drawthreedifferent typesof clustersparticipatedin at leastonediscussionAnswered aquestion thepresenteraskedINCORRECTLYAnswered aquestion thepresenteraskedCORRECTLYdidn'tfallasleep!clapped atthe end ofpresentationfinds amistake inthe slideAsked aquestion thepresenterdidn't knowthe answer todidn't usephone duringentirepresentationcan givea reasonfor usingclusteringanalysisknows how tochoose thenumber ofclusters in K-meansclusteringdidn't checkemail duringentirepresentationCan namethree basicclusteringalgorithmsknowsdifferencebetweencomplete andpartialclustering

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