Which of the following clustering methods is best suited for discovering non-glo
Practice Questions
Q1
Which of the following clustering methods is best suited for discovering non-globular shapes in data?
K-means
DBSCAN
Hierarchical clustering
Gaussian Mixture Models
Questions & Step-by-Step Solutions
Which of the following clustering methods is best suited for discovering non-globular shapes in data?
Step 1: Understand what clustering methods are. Clustering methods group similar data points together.
Step 2: Learn about different clustering methods. Some common methods include K-means, hierarchical clustering, and DBSCAN.
Step 3: Recognize that K-means works best for globular (spherical) shapes, meaning it assumes clusters are round.
Step 4: Understand that DBSCAN (Density-Based Spatial Clustering of Applications with Noise) can find clusters of various shapes and sizes.
Step 5: Realize that DBSCAN groups points that are close together and can identify clusters that are not round, making it suitable for non-globular shapes.
Step 6: Conclude that DBSCAN is the best choice for discovering non-globular shapes in data.
