Based on my prior knowledge, premature ventricular contractions (PVCs) are abnormal heartbeats that start in the ventricles, or lower chambers of the heart. PVCs can be a sign of heart disease or other underlying conditions, and can occur in individuals with or without a history of myocardial infarction (MI).

To analyze the relationship between the feature nr_02 (Premature ventricular contractions in the anamnesis) and the task of determining chronic heart failure, we can look at the possible values of nr_02 for each target class.

Let's assume we have a dataset with the following records:

| nr_02 | Chronic Heart Failure |
|-------|----------------------|
| no    | yes                  |
| yes   | no                   |
| yes   | yes                  |
| no    | no                   |
| no    | no                   |
| yes   | no                   |

Based on this data, we can create the dictionary with the following values:

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

Here, we see that for the target class "no" (indicating no chronic heart failure), the feature nr_02 has the value "no" in all the instances. On the other hand, for the target class "yes" (indicating chronic heart failure), the feature nr_02 has the value "yes" in all the instances.