B&B is an optimal algorithm of feature subset selection. The high computational complexity of this algorithm is its inherent problem. B&B algorithm constructs a search tree, and then searches for the optimal feature subset in the tree. The previous research on B&B algorithm focused on simplifying the search tree in order to reduce the search complexity, and several improvements have already existed. A theoretical analysis of basic B&B algorithm and the previous improvements are given under a common framework in which all the algorithms are compared. Based on this analysis, an improved B&B algorithm--BBPP+--is proposed. Experimental comparison shows that BBPP+ is more efficient than all previous algorithms.