Machine Learning - Ordinal target variable

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.

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

  1. A.A continuous target variable.
  2. B.A categorical target variable.
  3. C.An ordinal target variable.


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.).

I would like to ask why the answer to this question is not C when we are predicting the 5 most likely stocks to become acquisition targets (i.e there is ranking involved).

It’s not a well-worded question.

It appears that it’s meant to tell you that these five stocks (in no particular order) are the most likely targets. They’re focusing on the “in no particular order” part.

Questions on the real exam will be quite clear.

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