After analyzing the relationship between the feature "savings_status" and the task of determining whether a person receives a credit or not, we can create a dictionary that captures the possible values of the "savings_status" feature for each target class.

```json
{
	"yes": [">=1000"],
	"no": ["no known savings", "<100", "500<=X<1000", "100<=X<500"]
}
```

In this case, the only value of "savings_status" that is associated with the target class "yes" (person receives a credit) is ">=1000". On the other hand, for the target class "no" (person does not receive a credit), the possible values of "savings_status" are "no known savings", "<100", "500<=X<1000", and "100<=X<500".