Clustering

What is the main goal of clustering in data analysis?

• Predicting future values

• Dividing data into distinct groups

• Classifying data into predefined categories

• Finding the average of data points

Which of the following is a characteristic of partitioning methods?

• They create a hierarchy of clusters

• They partition the data into a fixed number of clusters

• They are based on density estimation

• They have overlapping clusters

Which method is best suited for creating a tree-like structure of clusters?

• K-Means

• DBSCAN

• Hierarchical Clustering

• Gaussian Mixture Models

What does DBSCAN stand for?

• Density-Based Spatial Clustering of Applications with Noise

• Distance-Based Spatial Clustering of Applications with Noise

• Data-Based Spatial Clustering of Applications with Noise

• Density-Based Sample Clustering of Applications with Noise

Which algorithm is typically used in partitioning methods?

• Single-linkage clustering

• DBSCAN

• K-Means

• Expectation-Maximization

In hierarchical clustering, what does "agglomerative" mean?

• • Starting with one cluster and splitting it

• • Starting with individual points and merging them

• Using a grid-based approach

• Forming clusters based on density

Which metric is commonly used to measure the similarity between points in clustering?

• • Euclidean distance

• • Manhattan distance

• • Cosine similarity

• All of the above

What is a key advantage of density-based clustering methods like DBSCAN?

• They require specifying the number of clusters in advance

• They can identify clusters of arbitrary shapes

• They are sensitive to the initial starting points

• They form a hierarchical tree structure

What is an outlier in the context of clustering?

• A data point that is central to a cluster

• A data point that does not belong to any cluster

• A data point that belongs to multiple clusters

• • A data point that changes clusters frequently

In K-Means clustering, what is the role of the "centroid"?

• It is the point farthest from all cluster members

• It is the average position of all the points in the cluster

• It is a randomly chosen point in the data

• It is a randomly chosen point in the data