Unit 3: Climatology - Practice Quiz

GEO295 — Physical Geography 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. -infinity to infinity
D. 0 to 1

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

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

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

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

4 The Dunn Index is defined as the ratio of:

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

5 Which clustering metric corrects the Rand Index for chance?

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

6 What does a Homogeneity score of 1.0 imply?

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

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

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

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

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

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

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

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

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

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 distance to the nearest cluster centroid
B. The mean intra-cluster distance (average distance to other points in the same cluster)
C. The mean nearest-cluster distance
D. The maximum diameter of the 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 exactly 0.5
B. Values near 0
C. Values near +1
D. Values near -1

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

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

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

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

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. Dunn Index
C. Silhouette Score
D. Homogeneity

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

25 A Davies-Bouldin Index of 0 indicates:

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

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

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

27 The Fowlkes-Mallows Index is bounded between:

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

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

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

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

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

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

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

A. V-measure
B. Dunn Index
C. Silhouette Score
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. There are outlier points
B. The clusters are random
C. The clusters perfectly match the ground truth (up to permutation)
D. The clusters are disjoint but incorrect

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. Homogeneity
B. NMI
C. Adjusted Rand Index
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. Clusters that have zero entropy
D. Points with positive silhouette scores

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

A. Yes, it favors a single cluster
B. It only works for k=2
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. NMI
B. Silhouette Score
C. ARI
D. FMI

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

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

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

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

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

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

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

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

A. The sample is on or very close to the decision boundary between two neighboring clusters
B. The sample is an outlier
C. The clustering is perfect
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 dataset is very small
B. The number of clusters is very large
C. The number of clusters is 1
D. The clustering and ground truth are highly correlated

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 average distance to the centroid
D. The maximum distance between any two points in the cluster

48 Which metric is strictly an Information Theoretic measure?

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

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

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

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

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