Based on prior knowledge and common sense, we can analyze the relationship between the feature "persons" and the task of rating the decision to buy a car.

Here is the analysis:

- Unacceptable: It is likely that the decision to buy a car would be considered unacceptable if the car's capacity in terms of persons to carry is limited. Therefore, the possible values of the feature "persons" for the target class "unacceptable" could be ['2'].

- Acceptable: The decision to buy a car would generally be considered acceptable if the car has sufficient capacity in terms of persons to carry. This could include cars with capacity for 2 or 4 persons. Therefore, the possible values of the feature "persons" for the target class "acceptable" could be ['2', '4'].

- Good: The decision to buy a car could be rated as good if the car has capacity for more than 4 persons. Therefore, the possible values of the feature "persons" for the target class "good" could be ['more'].

- Very Good: It is expected that cars with higher capacity in terms of persons to carry would be rated as very good. Therefore, the possible values of the feature "persons" for the target class "very good" could be ['4', 'more'].

Based on this analysis, we can generate the requested dictionary:

```json
{
	"unacceptable": ["2"],
	"acceptable": ["2", "4"],
	"very good": ["4", "more"],
	"good": ["more"]
}
```