Data Mining Week 7 Nptel Assignment Answers
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Data Mining Week 7 Nptel Assignment Answers (Jan-Apr 2025)
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- A good clustering is one having:
a) Low inter-cluster distance and low intra-cluster distance
b) Low inter-cluster distance and high intra-cluster distance
c) High inter-cluster distance and low intra-cluster distance
d) High inter-cluster distance and high intra-cluster distance
- Which of the following is an exploratory data mining technique?
a) Classification
b) Clustering
c) Regression
d) None of the above
- Which of the following is a hierarchical clustering algorithm?
a) Single linkage clustering
b) K-means clustering
c) DBSCAN
d) None of the above
- Which of the following clustering algorithm uses a dendogram?
a) Complete linkage clustering
b) K-means clustering
c) DBSCAN
d) None of the above
- Which of the following clustering algorithm uses a minimal spanning tree?
a) Complete linkage clustering
b) Single linkage clustering
c) Average linkage clustering
d) DBSCAN
- Distance between two clusters in single linkage clustering is defined as:
a) Distance between the closest pair of points between the clusters
b) Distance between the furthest pair of points between the clusters
c) Distance between the most centrally located pair of points in the clusters
d) None of the above
Data Mining Week 7 Nptel Assignment Answers
- Distance between two clusters in complete linkage clustering is defined as:
a) Distance between the closest pair of points between the clusters
b) Distance between the furthest pair of points between the clusters
c) Distance between the most centrally located pair of points in the clusters
d) None of the above
- Consider a set of five 2-dimensional points p1=(0, 0), p2=(0, 1), p3=(5, 8), p4=(5, 7), and p5=(0, 0.5). Euclidean distance is the distance function. Single linkage clustering is used to cluster the points into two clusters. The clusters are:
a) {p1, p2, p3} {p4, p5}
b) {p1, p4, p5} {p2, p3}
c) {p1, p2, p5} {p3, p4}
d) {p1, p2, p4} {p3, p5}
- Which of the following is not true about K-means clustering algorithm?
a) It is a partitional clustering algorithm
b) The final cluster obtained depends on the choice of initial cluster centres
c) Number of clusters need to be specified in advance
d) It can generate non-convex cluster shapes
- Consider a set of five 2-dimensional points p1=(0, 0), p2=(0, 1), p3=(5, 8), p4=(5, 7), and p5=(0, 0.5). Euclidean distance is the distance function. The k-means algorithm is used to cluster the points into two clusters. The initial cluster centers are p1 and p4. The clusters after two iterations of k-means are:
a) {p1, p4, p5} {p2, p3}
b) {p1, p2, p5} {p3, p4}
c) {p3, p4, p5} {p1, p2}
d) {p1, p2, p4} {p3, p5}
- Which of the following is not true about the DBSCAN algorithm?
a) It is a density based clustering algorithm
b) It requires two parameters MinPts and epsilon
c) The number of clusters need to be specified in advance
d) It can produce non-convex shaped clusters
Data Mining Week 7 Nptel Assignment Answers
For answers to others Nptel courses, please refer to this link: NPTEL Assignment
