NO.PZ2016082405000014
问题如下：
Using the properties of firms that have already fallen into default/non-default groups to categorize a new observation by how closely it resembles the members already in each of the groups is referred to as:
选项：
A.linear discriminant analysis.
B.the k-nearest neighbor approach.
C.support vector machines.
D.None of the above.
解释：
The K-nearest neighbor is a nonparametric discriminant technique that uses the properties of firms that already have fallen into the categories of interest, and it categorizes a new entrant by how close it resembles the members already in each of the groups.
how closely it resembles the members already in each of the groups。这里说的是距离每个group的点有多近，不是说最近同类的members有多少个，描述更像是支持向量机吧？虽然看得到课件说的，但是K-临近法，不是更需要强调一个圈圈内有多少个同类吗，而不是多近
