Asked aquestion thepresenterdidn't knowthe answer toparticipatedin at leastonediscussioncan statedifference betweenexclusive,overlapping, andfuzzy clusteringdidn't checkemail duringentirepresentationcan givea reasonfor usingclusteringanalysiscan draw thedifferencebetweenhierarchical &partitionalclusteringSaid helloto onlinestudentsBrought thereadingmaterialsto classAsked aquestion thepresenterdidn't knowthe answer toAsked aquestion thatconfusedeverybodydidn'tfallasleep!clapped atthe end ofpresentationfinds amistake inthe slideAsked afollow upquestionto aquestionCan namethree basicclusteringalgorithmsknowsdifferencebetweencomplete andpartialclusteringcan describethe ideabehind K-meansclusteringAnswered aquestion thepresenteraskedINCORRECTLYGave ausefulexample toexplain aconceptReadingmaterialshaveannotationsand highlightsdidn't usephone duringentirepresentationcan describeand drawthreedifferent typesof clustersAnswered aquestion thepresenteraskedCORRECTLYknows how tochoose thenumber ofclusters in K-meansclusteringAsked aquestion thepresenterdidn't knowthe answer toparticipatedin at leastonediscussioncan statedifference betweenexclusive,overlapping, andfuzzy clusteringdidn't checkemail duringentirepresentationcan givea reasonfor usingclusteringanalysiscan draw thedifferencebetweenhierarchical &partitionalclusteringSaid helloto onlinestudentsBrought thereadingmaterialsto classAsked aquestion thepresenterdidn't knowthe answer toAsked aquestion thatconfusedeverybodydidn'tfallasleep!clapped atthe end ofpresentationfinds amistake inthe slideAsked afollow upquestionto aquestionCan namethree basicclusteringalgorithmsknowsdifferencebetweencomplete andpartialclusteringcan describethe ideabehind K-meansclusteringAnswered aquestion thepresenteraskedINCORRECTLYGave ausefulexample toexplain aconceptReadingmaterialshaveannotationsand highlightsdidn't usephone duringentirepresentationcan describeand drawthreedifferent typesof clustersAnswered aquestion thepresenteraskedCORRECTLYknows how tochoose thenumber ofclusters in K-meansclustering

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.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
  1. Asked a question the presenter didn't know the answer to
  2. participated in at least one discussion
  3. can state difference between exclusive, overlapping, and fuzzy clustering
  4. didn't check email during entire presentation
  5. can give a reason for using clustering analysis
  6. can draw the difference between hierarchical & partitional clustering
  7. Said hello to online students
  8. Brought the reading materials to class
  9. Asked a question the presenter didn't know the answer to
  10. Asked a question that confused everybody
  11. didn't fall asleep!
  12. clapped at the end of presentation
  13. finds a mistake in the slide
  14. Asked a follow up question to a question
  15. Can name three basic clustering algorithms
  16. knows difference between complete and partial clustering
  17. can describe the idea behind K-means clustering
  18. Answered a question the presenter asked INCORRECTLY
  19. Gave a useful example to explain a concept
  20. Reading materials have annotations and highlights
  21. didn't use phone during entire presentation
  22. can describe and draw three different types of clusters
  23. Answered a question the presenter asked CORRECTLY
  24. knows how to choose the number of clusters in K-means clustering