Based on the given feature description, it appears that the feature "credit_history" represents the credit history of a person. To analyze the relationship between this feature and the task of whether the person receives a credit or not, we can determine the possible values of the "credit_history" feature for each target class.

After examining the data, we find the following relationships:

Possible values of feature credit_history for target class yes: 
- 'existing paid'
- 'delayed previously'
- 'no credits/all paid'
- 'all paid'

Possible values of feature credit_history for target class no: 
- 'critical/other existing credit'

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

```json
{
	"yes": ["existing paid", "delayed previously", "no credits/all paid", "all paid"],
	"no": ["critical/other existing credit"]
}
```