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Clustering - The Data Ensemble MCQs Solution | TCS Fresco Play

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


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

Jaccard Distance

3.Unsupervised learning focuses on understanding the data and its underlying pattern.


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


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


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


7. A centroid is a valid point in a non-Eucledian space .


8. What is the overall complexity of the the Agglomerative Hierarchical Clustering ?

O(N^3) O(N2 logN)

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


10. ___________ measures the goodness of a cluster


11. ___________ is the data point that is closest to the other point in the cluster.


12. _____________ is when points don't move between clusters and centroids stabilize.


13. Sampling is one technique to pick the initial k points in K Means Clustering


14. Hierarchical Clustering is a suggested approach for Large Data Sets


15. K Means algorithm assumes Eucledian Space/Distance


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


17. ___________ is a way of finding the k value for k means clustering.

cross validation

18. Each Round----- O(NK)



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