Hands-On Unsupervised Learning with Python

Chapter 5

1. Hard clustering is based on fixed assignments; hence, a sample x_i will always belong to a single cluster. Conversely, soft clustering returns a degree vector whose elements represent the membership level, with respect to each cluster (for example, (0.1, 0.7, 0.05, 0.15)).
2. No; fuzzy c-means is an extension of k-means, and it's not particularly suitable for non-convex geometries. However, the soft assignments allow for evaluating the influence of neighboring clusters.
3. The main assumption is that the dataset has been drawn from a distribution that can be efficiently approximated with the weighted sum of a number of Gaussian distributions.
4. It means that the first model has a number of parameters that is the double of the second one. ...