NPTEL Data Mining Assignment Answers 2023 -Week 7

Are you a student struggling with the Data Mining NPTEL Week 7 assignment? Look no further! In this article, we have compiled a set of hints and answers to help guide you through the assignment.

Make sure to give it a try on your own first, but use these hints as a helpful resource.

NPTEL DATA MINING ASSIGNMENT ANSWERS 2023 -WEEK 7

Q1. Which of the following statement is NOT true about clustering?

Answer: (a) It is a supervised learning technique

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Q2. Which of the following clustering technique start with the points as individual clusters and, at each step, merge the closest pair of clusters

Answer: (d) Agglomerative clustering

Q3. DBSCAN is a___________ algorithm

Answer: (a) Partitional clustering

Q4. The Euclidean distance matrix between four 2-dimensional points, p1, p2, p3, and p4, is shown below. A possible set of co-ordinate values of these points are:

Answer: (d) p1=(0, 0), p2=(1, 1), p3=(1, 0), p4=(0, 1)

Q5. The leaves of a dendogram in hierarchical clustering represent?

Answer: (a) Individual data points

Q6. Distance between two clusters in complete linkage clustering is defined as:

Answer: (b) Distance between the furthest pair of points between the clusters

Q7. Consider a set of five 2-dimensional points p1=(0, 0), p2=(5, 0), p3=(5, 1), p4=(0, 1), and p5=(0, 0.5). Euclide-an distance is the distance function. Single linkage clustering is used to cluster the points into two clusters. The clusters are:

Answer: (d) {p1, p2, p4} {p3, p5}

Q8. Consider a set of five 2-dimensional points p₁=(0, 0), p₂=(5, 0), p₃=(5, 1), p₄=(0, 1), and p₅=(0, 0.5). Euclide-an distance is the distance function. Complete linkage clustering is used to cluster the points into two clus-ters. The clusters are:

Answer: (a) {p1, p4, p5} {p2, p3}

Q9. Consider a set of five 2-dimensional points p₁=(0, 0), p₂=(5, 0), p₃=(5, 1), p₄=(0, 1), 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 p5. The clusters after two iterations of k-means are:

Answer: (b) {p1, p2, p3} {p4, p5}

Q10. Given a set of seven 2-dimensional points p₁=(0, 0), p₂=(5, 0), p₃=(5, 1), p₄=(0, 1), p₅=(0, 0.5), p₆=(0, 9), and p₇=(5.5, 1). Euclidean distance is the distance function. The DBSCAN algorithm is used to cluster the points. Epsilon = 1, and MinPts = 2 is used for DBSCAN. The clusters and outliers obtained are:

Answer: (c) Clusters: {p1, p4, p5} {p2, p3, p7}; Outlier: p6

Disclaimer: Please keep in mind that these answers are intended to serve as a reference for students. Our website does not guarantee the accuracy of the answers provided. We encourage all students to complete their assignments independently and use these answers as a supplement to their own understanding.

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