Detailed Instructions: In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Q: In this paper the behavior of various be lief network learning algorithms is stud ied. Selecting belief networks with cer tain minimallity properties turns out to be NP-hard, which justifies the use of search heuristics. Search heuristics based on the Bayesian measure of Cooper and Her skovits and a minimum description length (MDL) measure are compared with re spect to their properties for both limit ing and finite database sizes. It is shown that the MDL measure has more desir able properties than the Bayesian mea sure. Experimental results suggest that for learning probabilities of belief net works smoothing is helpful.
A:
Properties of Bayesian Belief Network Learning Algorithms