Reading Questions for Lecture 8
Clustering (Ch. 7.1-7.4, 7.8)
- (Gavin) From page 144: k-means clustering is a special case of EM. In geometric terms, k-means can be viewed as a circle, and EM as an ellipse. Can k-means's single parameter be considered the radius of the circle, and EM's two parameters the defining values (whatever they're called) for the ellipse?
- (Matthew) When is clustering most effective at preprocessing data?
- (Ron) Explain a little better that an increase in expectation implies an increase in the incomplete likelihood?
- (Roice) From the extra credit problem, what is the COBWEB clustering algorithm?