Unit 3 - Practice Quiz

GEO295 50 Questions
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1 What is the range of values for the Silhouette Score?

A. -1 to 1
B. 0 to infinity
C. 0 to 1
D. -infinity to infinity

2 Which of the following metrics does NOT require ground truth labels (true class labels) to evaluate clustering performance?

A. Fowlkes-Mallows Index
B. Silhouette Score
C. Adjusted Rand Index
D. Normalized Mutual Information

3 In the context of the Davies-Bouldin Index, a lower value indicates:

A. Worse clustering
B. High computational cost
C. Better clustering
D. Overfitting

4 The Dunn Index is defined as the ratio of:

A. Maximum inter-cluster distance to minimum intra-cluster distance
B. Mean intra-cluster distance to mean inter-cluster distance
C. Minimum inter-cluster distance to maximum intra-cluster distance
D. Variance of clusters to bias of clusters

5 Which clustering metric corrects the Rand Index for chance?

A. Adjusted Rand Index (ARI)
B. Completeness Score
C. Fowlkes-Mallows Index
D. Silhouette Score

6 What does a Homogeneity score of 1.0 imply?

A. The number of clusters equals the number of samples
B. The clusters overlap significantly
C. All clusters contain data points from only a single class
D. All data points of a specific class are assigned to the same cluster

7 If all data points belonging to a given class are elements of the same cluster, which metric is maximized?

A. Silhouette Score
B. Completeness
C. Homogeneity
D. Dunn Index

8 The V-measure is the harmonic mean of which two metrics?

A. Silhouette and Dunn Index
B. ARI and NMI
C. Homogeneity and Completeness
D. Precision and Recall

9 Which metric is calculated as the geometric mean of pairwise precision and pairwise recall?

A. Adjusted Mutual Information
B. Davies-Bouldin Index
C. Fowlkes-Mallows Index
D. V-measure

10 Normalized Mutual Information (NMI) is often preferred over Mutual Information (MI) because:

A. MI yields negative values
B. NMI scales the result between 0 and 1, making it comparable across datasets
C. NMI does not require ground truth
D. MI is computationally too expensive

11 What is the primary advantage of Adjusted Mutual Information (AMI) over Normalized Mutual Information (NMI)?

A. AMI is faster to compute
B. AMI works without ground truth
C. AMI can handle negative values
D. AMI accounts for chance (randomness) in cluster assignment

12 In the Silhouette Score formula s = (b - a) / max(a, b), what does 'a' represent?

A. The maximum diameter of the cluster
B. The distance to the nearest cluster centroid
C. The mean nearest-cluster distance
D. The mean intra-cluster distance (average distance to other points in the same cluster)

13 Which of the following indicates a clustering result where samples have been assigned to the wrong clusters according to the Silhouette Score?

A. Values near -1
B. Values exactly 0.5
C. Values near 0
D. Values near +1

14 The Adjusted Rand Index (ARI) yields a score of approximately 0 when:

A. The clustering is independent/random compared to the ground truth
B. The clustering is perfect
C. The number of clusters is equal to the number of samples
D. The clustering is identical to the ground truth

15 Which metric is most sensitive to noise and outliers because it uses maximum diameters and minimum separations?

A. V-measure
B. Dunn Index
C. Silhouette Score
D. Adjusted Rand Index

16 If a clustering algorithm produces 100 clusters for a dataset of 100 samples (each sample is its own cluster), which metric will naturally maximize to 1.0, potentially giving a misleading impression of quality?

A. Completeness
B. Homogeneity
C. Dunn Index
D. Silhouette Score

17 Conversely, if all samples are assigned to a single cluster, which metric will maximize to 1.0?

A. Silhouette Score
B. Homogeneity
C. Davies-Bouldin Index
D. Completeness

18 What is the beta parameter used for in the V-measure calculation?

A. To normalize the dataset
B. To define the number of clusters
C. To adjust for chance
D. To weight the importance of Homogeneity versus Completeness

19 When calculating the Fowlkes-Mallows Index, 'TP' (True Positive) refers to:

A. Clusters that are perfectly pure
B. Points correctly classified as noise
C. Pairs of points that are in the same cluster in both the true labels and predicted labels
D. Pairs of points that are in different clusters in both labels

20 Which of the following is an 'Internal' clustering validity index?

A. Normalized Mutual Information
B. Davies-Bouldin Index
C. Adjusted Rand Index
D. V-measure

21 What is a major limitation of the Silhouette Score when dealing with non-convex clusters (e.g., ring shapes)?

A. It tends to give lower scores to density-based clusters that are not spherical
B. It is computationally cheap
C. It cannot handle negative values
D. It requires ground truth

22 Which component of the Silhouette Score represents the 'separation' of the cluster?

A. max(a, b)
B. b - a
C. b (nearest-cluster distance)
D. a (intra-cluster distance)

23 In the context of NMI, Entropy is used to measure:

A. The geometric shape of the cluster
B. The uncertainty associated with the class or cluster distribution
C. The number of outliers
D. The distance between centroids

24 Which metric is symmetric (i.e., Metric(A, B) = Metric(B, A))?

A. Completeness
B. Silhouette Score
C. Adjusted Rand Index
D. Homogeneity

25 A Davies-Bouldin Index of 0 indicates:

A. Infinite variance
B. Ideally separated and compact clusters
C. The worst possible clustering
D. Random clustering

26 Which of the following is required to calculate the Adjusted Mutual Information (AMI)?

A. Ground truth labels and predicted labels
B. Centroids of the clusters
C. Euclidean distance matrix
D. Only the predicted labels

27 The Fowlkes-Mallows Index is bounded between:

A. -infinity to +infinity
B. -1 and 1
C. 0 and infinity
D. 0 and 1

28 Why might the Dunn Index be computationally expensive for large datasets?

A. It requires ground truth labels
B. It involves complex integrals
C. It requires calculating eigenvalues
D. It requires calculating pairwise distances between all points to find min/max distances

29 When interpreting Homogeneity (H) and Completeness (C), if H is high and C is low, what does this usually suggest?

A. The data is random noise
B. The clustering is perfect
C. The algorithm merged distinct classes into one cluster
D. The algorithm over-segmented the classes (many small clusters for one class)

30 In the formula for NMI, the Mutual Information I(U, V) is normalized by:

A. The number of samples
B. The maximum distance in the dataset
C. The variance of U and V
D. The arithmetic or geometric mean of the entropies of U and V

31 What happens to the Adjusted Rand Index (ARI) if the class labels are permuted (renamed)?

A. The score becomes zero
B. The score changes drastically
C. The score remains the same
D. The score becomes negative

32 Which external metric suffers less from the 'curse of dimensionality' in its calculation logic (though distances themselves might suffer)?

A. V-measure
B. Silhouette Score
C. Dunn Index
D. Davies-Bouldin Index

33 For a dataset with 'k' ground truth classes, if a clustering algorithm produces 'k' clusters and ARI is 1.0, this means:

A. The clusters perfectly match the ground truth (up to permutation)
B. The clusters are random
C. The clusters are disjoint but incorrect
D. There are outlier points

34 Which metric would be most appropriate to select the optimal number of clusters 'k' in K-Means clustering when true labels are unknown?

A. Adjusted Rand Index
B. NMI
C. Homogeneity
D. Silhouette Score

35 In the calculation of the Davies-Bouldin Index, 'scatter' refers to:

A. The average distance of points in a cluster to their centroid
B. The distance between cluster centroids
C. The total number of points
D. The entropy of the cluster

36 The Rand Index (RI) calculates the percentage of:

A. Correctly classified centroids
B. Decisions where pairs of data points are correctly agreed upon (together or apart)
C. Points with positive silhouette scores
D. Clusters that have zero entropy

37 Does the V-measure prefer a specific number of clusters?

A. It only works for k=2
B. Yes, it favors a single cluster
C. Yes, it favors a large number of clusters if not adjusted
D. No, it is independent of cluster count

38 Which metric is based on the idea that good clusters should be highly similar internally and highly dissimilar externally?

A. Silhouette Score
B. NMI
C. FMI
D. ARI

39 If two different clustering algorithms produce the exact same partition of data, the AMI score between them will be:

A. Infinity
B. 0.5
C. 0
D. 1

40 Which of the following metrics is NOT bounded by 1 (i.e., can it be greater than 1)?

A. Silhouette Score
B. Adjusted Rand Index
C. V-measure
D. Davies-Bouldin Index

41 Homogeneity is equivalent to which classification metric when applied to clusters?

A. Recall
B. Accuracy
C. F1 Score
D. Precision

42 Completeness is equivalent to which classification metric when applied to clusters?

A. Specificity
B. Recall
C. Precision
D. Accuracy

43 Which metric assumes that the best clustering has the minimum sum of similarities between each cluster and its most similar one?

A. Silhouette Score
B. Davies-Bouldin Index
C. Calinski-Harabasz Index
D. Dunn Index

44 When using the Silhouette Score, a value of 0 implies:

A. The clustering is perfect
B. The sample is on or very close to the decision boundary between two neighboring clusters
C. The sample is an outlier
D. The sample is far away from all clusters

45 Why is 'Adjusted' Mutual Information preferred over 'Normalized' Mutual Information in many comparative studies?

A. It is easier to calculate
B. It does not use logarithms
C. It corrects for the bias toward clusters with many partitions (high k)
D. It is always positive

46 The Fowlkes-Mallows index is generally higher when:

A. The clustering and ground truth are highly correlated
B. The number of clusters is very large
C. The dataset is very small
D. The number of clusters is 1

47 In the Dunn Index, the 'diameter' of a cluster usually refers to:

A. The radius of the cluster
B. The distance to the nearest neighbor
C. The maximum distance between any two points in the cluster
D. The average distance to the centroid

48 Which metric is strictly an Information Theoretic measure?

A. Dunn Index
B. Silhouette Score
C. Davies-Bouldin Index
D. Normalized Mutual Information (NMI)

49 If a dataset has highly imbalanced classes, which pair of metrics gives a good view of cluster purity and class coverage?

A. Homogeneity and Completeness
B. Mean and Median
C. Dunn and Variance
D. Silhouette and DBI

50 A negative value for the Adjusted Rand Index (ARI) implies:

A. The clustering is perfect
B. The clustering is random
C. ARI cannot be negative
D. The clustering is worse than random assignment