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little_back · 2019年12月29日

问一道题:NO.PZ2015120204000033

问题如下:

Paul suggests the following step which would be repeated every quarter.

Step 3 For each of the 20 different groups, we use labeled data to train a model that will predict the five stocks (in any given group) that are most likely to become acquisition targets in the next one year.

The target variable for the labelled training data to be used in Step 3 is most likely which one of the following?

选项:

A.

A continuous target variable.

B.

A categorical target variable.

C.

An ordinal target variable.

解释:

B is correct. To predict which stocks are likely to become acquisition targets, the ML model would need to be trained on categorical labelled data having the following two categories: “0” for “not acquisition target”, and “1” for “acquisition target”.

A is incorrect, because the target variable is categorical, not continuous.

C is incorrect, because the target variable is categorical, not ordinal (i.e., 1st, 2nd, 3rd, etc.).

为什么不是C?

2 个答案
已采纳答案

星星_品职助教 · 2019年12月31日

补充一下,这道题本质上还是一个分类的问题,可以关联一下此前回归中学到的Y变量是dummy variable的情况,例如probit或logit模型。Y的取值设定为被收购就是1,不被收购就是0。这道题想问的就是找到5个1就行。而这5个1里面就不用再排序了。

以上的做法可以通过例如设置不同的收购门槛值来实现,如果一开始回归的结果发现有10个1,那么说明门槛设低了。可以提高门槛再做一次,如果这次只有4个1,说明设高了。以此类推,直到只剩5个1。这5家公司就是最有可能被收购的5家,而这个过程里是不涉及到5家公司内部再排序的。

如果想考ordinal variable,题干中会额外说明需要按照一个特定标准(例如概率大小,满足条件多少)来进行排序。没有特殊说明的话,就直接选择分类变量即可,加油。

星星_品职助教 · 2019年12月30日

同学你好,
Ordinal variable指的是排序,这道题里只需要找到5只股票就完成任务了,而不需要将这5只股票再进行内部排序了。所以直接选B即可