Therefore, the choice of the right classifier for a specific recommending task still
has nowadays much of exploratory. A practical rule-of-thumb is to start with the
simplest approach and only introduce complexity if the performance gain obtained
justifies it. The performance gain should of course balance different dimensions
such as prediction accuracy or computational efficiency.