Introduction To Machine Learning IIT-KGP Nptel Week 8 Assignment Answers
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Introduction To Machine Learning IIT-KGP Nptel Week 8 Assignment Answers
Introduction To Machine Learning IIT-KGP Week 8 Answers (July-Dec 2024)
Q1.‘Do the clustering results of the K-Means algorithm depend on the initial cluster centroid choices? A) Yes B) No
Answer: A) Yes
Q2‘Which of the following can act as possible termination conditions in K-Means? I. Assignment of observations to clusters does not change between iterations. Except for cases with a bad local minimum. II. Centroids do not change between successive iterations. A) I only B) II only C) l and II
Q3Assume, you want to cluster 7 observations into 3 clusters using K-Means clustering algorithm. After first iteration the clusters: C1, C2, C3 has the following observations: C1:{(1,2), (4,4), (7,7)} C2:{(0,4), (4,0)} €3:{(5,5), (9,9)} What will be the cluster centroids after the first iteration?
A) C1: (4,4), C2: (2,2), C3: (7,7)
B) C1: (2,2), C2: (0,0), C3: (5,5)
C) C1: (6,6), C2: (4,4), C3: (9,9)
D) None of these
Answer: A) C1: (4,4), C2: (2,2), C3: (7,7)
Q4.In single-link clustering, the similarity of two clusters is the similarity of their most similar members. What is the time complexity of the single-link clustering algorithm? (Note: n is the number of data points) A) O(n2) B) o(n2log n) c) o(n3log n) D) O(n3)
Q7.Which of the following is not a clustering approach? A) Hierarchical B) Partitioning C) Bagging D) Density-Based
Answer: C) Bagging
Q8.In which of the following cases will K-Means clustering fail to give good results? A) Data points with outliers B) Data points with round shapes C) Data points with non-convex shapes D) Data points with different densities
Answer: A) Data points with outliers C) Data points with non-convex shapes D) Data points with different densities
Q10.‘Which of the following statements is/are not true about k-means clustering? A) It is an unsupervised learning algorithm B) Overlapping of clusters is allowed in k-means clustering C) It is a hard-clustering technique D) k is a hyperparameter in k-means
Answer: B) Overlapping of clusters is allowed in k-means clustering
1) For two runs of K-Mean clustering is it expected to get same clustering results? A. Yes B. No
Answer: A
2) Which of the following can act as possible termination conditions in K-Means? I. For a fixed number of iterations. II Assignment of observations to clusters does not change between iterations. Except for cases with a bad local minimum. III Centroids do not change between successive iterations. IV. Terminate when RSS falls below a threshold A) I, III and IV B) I, II and III C) I, II and IV D) All of the above
Answer: D) All of the above
These are solutions for Nptel Introduction To ML IITKGP ASSIGNMENT 8 Answers
3) After performing K-Means Clustering analysis on a dataset, you observed the following dendrogram. Which of the following conclusion can be drawn from the dendrogram?
A) There were 28 data points in clustering analysis. B) The best no. of clusters for the analysed data points is 4. C) The proximity function used is Average-link clustering. D) The above dendrogram interpretation is not possible for K-Means clustering analysis.
Answer: D) The above dendrogram interpretation is not possible for K-Means clustering analysis.
4) What should be the best choice of no. of clusters based on the following results :
A. 1 B. 2 C. 3 D. 4
Answer: C. 3
These are solutions for Nptel Introduction To ML IITKGP ASSIGNMENT 8 Answers
5) Given, six points with the following attributes : Which of the following clustering representations and dendrogram depicts the use of MIN or Single link proximity function in hierarchical clustering :
Answer: A
6) Is it possible that assignment of observations to clusters does not change between successive iterations of K-means? A) Yes B) No C) Can’t say D) None of these
7) What is the possible reason(s) for producing two different dendograms using agglomerative clustering for the same data set? A) Proximity function B) No. of data points C) Variables used D) All of these
Answer: D) All of these
These are solutions for Nptel Introduction To ML IITKGP ASSIGNMENT 8 Answers
8) Which of the following algorithms suffer from the problem of convergence at local optima? I) K-means clustering II) Agglomerative clustering III) Expectation-minimization clustering IV) Divisive clustering A) I and II B) II and III C) III nad IV D) I and III
Answer: D) I and III
9) Which of the following is/are valid iterative strategy before performing clustering analysis for treating missing values? A) Imputation with mean B) Nearest neighbour assignment C) Imputation with expectation-maximization algorithm D) None of these
Answer: C) Imputation with expectation-maximization algorithm
10) If two variables V1 and V2 are used for clustering, which of the following is/are true with K means clustering algorithm for K=3? I) If V1 and V2 have a correlation of 1, cluster centroid will be in a straight line. II) If V1 and V2 have a correlation of 0, cluster centroid will be in a straight line. A) I only B) II only C) I and II D) None of these
Answer: A) I only
These are solutions for Nptel Introduction To ML IITKGP ASSIGNMENT 8 Answers
