How do I choose the right segmentation algorithm?

What factors should I consider when choosing a segmentation algorithm?

You should consider the type of data you have, the desired outcome, and the complexity of the algorithm.

Can you explain the difference between K-means and hierarchical clustering?

K-means is faster and works well with large datasets, while hierarchical clustering provides a tree-like structure for smaller datasets.

Which algorithm is better for image segmentation?

For image segmentation, algorithms like U-Net or Mask R-CNN are often preferred due to their accuracy in pixel-level classification.

How do I evaluate the performance of a segmentation algorithm?

You can evaluate performance using metrics like silhouette score, Davies-Bouldin index, or visual inspection of the segmented output.