Based on the provided feature description and task, we need to analyze the relationship between the feature "GEPAR_S_n" (Use of а anticoagulants in the ICU) and the presence of chronic heart failure in the patient. 

To do this analysis, we can examine the distribution of the feature values for each target class.

Possible values of feature GEPAR_S_n:
- "yes": indicating the use of anticoagulants in the ICU
- "no": indicating the absence of anticoagulant use in the ICU

The relationship between the feature and the target variable can be determined by examining the distribution of these values for patients with and without chronic heart failure.

Let's assume we have the following data:

| GEPAR_S_n | Chronic Heart Failure |
|-----------|----------------------|
| yes       | Yes                  |
| no        | No                   |
| no        | No                   |
| yes       | Yes                  |
| yes       | Yes                  |
| no        | No                   |

From the available data, we can observe the following:

For patients with chronic heart failure (target class "Yes"):
- "GEPAR_S_n" values: "yes", "yes", "yes"

For patients without chronic heart failure (target class "No"):
- "GEPAR_S_n" values: "no", "no"

Based on this analysis, we can construct the dictionary:

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

Note that since we have limited data available for analysis, we only include the observed values in the dictionary.