Based on my prior knowledge, I will analyze the relationship between the feature "GEPAR_S_n" (Use of а anticoagulants in the ICU) and the occurrence of chronic heart failure.

To do this, I will examine the distribution of the feature values for each target class and determine if there is a significant association between the feature and the presence of chronic heart failure.

Here is the generated dictionary based on the analysis:

```json
{
	"no": ["yes"],
	"yes": ["no"]
}
```

Since the feature "GEPAR_S_n" represents the use of anticoagulants in the ICU, it is likely that patients who have chronic heart failure would require anticoagulant therapy. Therefore, for cases where chronic heart failure is not present (target class "no"), the possible values for the feature "GEPAR_S_n" are ["yes"]. Conversely, in cases where chronic heart failure is present (target class "yes"), the possible values for the feature "GEPAR_S_n" are ["no"].

Please note that this analysis assumes there is a clear relationship between the feature "GEPAR_S_n" and chronic heart failure. If there is limited or inconclusive data suggesting such a relationship, the values for each target class in the dictionary may be different or more limited.