Introduction to Machine Learning Nptel Week 10 Answers
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Introduction to Machine Learning Nptel Week 10 Answers (Jan-Apr 2025)
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1. Which of the option shows the hierarchy of clusters created by the single link clustering algorithm for the given pairwise distance matrix?
a. Option A
b. Option B
c. Option C
d. Option D
2. For the pairwise distance matrix given in the previous question, which of the following shows the hierarchy of clusters created by the complete link clustering algorithm?
a. Option A
b. Option B
c. Option C
d. Option D
3. In BIRCH, using number of points NN, sum of points SUMSUM, and sum of squared points SSSS, we can determine the centroid and radius of the combination of any two clusters A and B. How do you determine the radius of the combined cluster?
a. Radius=SSANA−(SUMANA)2+SSBNB−(SUMBNB)2Radius = \sqrt{ \frac{SS_A}{N_A} – \left(\frac{SUM_A}{N_A}\right)^2 + \frac{SS_B}{N_B} – \left(\frac{SUM_B}{N_B}\right)^2 }
b. Radius=SSANA−(SUMANA)2+SSBNB−(SUMBNB)2Radius = \sqrt{ \frac{SS_A}{N_A} – \left(\frac{SUM_A}{N_A}\right)^2 } + \sqrt{ \frac{SS_B}{N_B} – \left(\frac{SUM_B}{N_B}\right)^2 }
c. Radius=SSA+SSBNA+NB−(SUMA+SUMBNA+NB)2Radius = \sqrt{ \frac{SS_A + SS_B}{N_A + N_B} – \left(\frac{SUM_A + SUM_B}{N_A + N_B}\right)^2 }
d. Radius=SSANA+SSBNB−(SUMA+SUMBNA+NB)2Radius = \sqrt{ \frac{SS_A}{N_A} + \frac{SS_B}{N_B} – \left(\frac{SUM_A + SUM_B}{N_A + N_B}\right)^2 }
4. Statement 1: CURE is robust to outliers.
Statement 2: Because of multiplicative shrinkage, the effect of outliers is dampened.
a. Statement 1 is true. Statement 2 is true. Statement 2 is the correct reason for statement 1.
b. Statement 1 is true. Statement 2 is true. Statement 2 is not the correct reason for statement 1.
c. Statement 1 is true. Statement 2 is false.
d. Both statements are false.
5. Run K-means on the input features of the MNIST dataset using the following initialization:
KMeans(n_clusters=10, random_state=seed). What is the accuracy of the resulting labels?
a. 0.790
b. 0.893
c. 0.702
d. 0.933
Introduction to Machine Learning Nptel Week 10 Answers
6. For the same clusters obtained in the previous question, calculate the rand-index.
a. 0.879
b. 0.893
c. 0.919
d. 0.933
7. In rand-index calculation, aa represents true positives (pairs of points belonging to the same cluster), and bb represents true negatives (pairs of points belonging to different clusters). How are the rand-index and accuracy related?
a. rand-index = accuracy
b. rand-index = 1.18×1.18 \times accuracy
c. rand-index = accuracy/2
d. None of the above
8. Run BIRCH on the input features of the MNIST dataset using Birch(n_clusters=10, threshold=1). What is the rand-index obtained?
a. 0.91
b. 0.96
c. 0.88
d. 0.98
Introduction to Machine Learning Nptel Week 10 Answers
9. Run PCA on the MNIST dataset input features with n_components=2. Now run DBSCAN using DBSCAN(eps=0.5, min_samples=5) on both the original features and the PCA features. What are their respective number of outliers/noisy points detected by DBSCAN?
a. 1600, 1522
b. 1500, 1482
c. 1000, 1000
d. 1797, 1742
Introduction to Machine Learning Nptel Week 10 Answers
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