Basics of Clustering(Machine Learning)

Q.Which learning is the method of finding structure in the data without labels.

  • Active
  • Supervised
  • Unsupervised

Q.Members of the same cluster are far away / distant from each other .

  • True
  • False

Q.The number of rounds for convergence in k means clustering can be lage

  • True
  • False

Q.What is a preferred distance measure while dealing with sets ?

  • Eucleadian
  • Jaccard
  • Manhattan

Q.The ______ is a visual representation of how the data points are merged to form clusters.

  • Dendogram
  • Scatter Plot
  • Graph

Q.___________ measures the goodness of a cluster

  • Clusteroid
  • Centroid
  • Cohesion

Q.___________ of two points is the average of the two points in Eucledian Space.

  • Centroid
  • Central Tendency
  • Center

Q.Each point is a cluster in itself. We then combine the two nearest clusters into one. What type of clustering does this represent ?

  • Divisive
  • Agglomerative
  • Point Assignment

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