Based on prior knowledge, the feature "nr_02", which represents premature ventricular contractions in the anamnesis, could potentially be related to the presence of chronic heart failure in the myocardial infarction complications data.

To analyze the relationship between the feature and the task, we need to consider how the different values of "nr_02" are associated with the presence or absence of chronic heart failure.

Let's assume that "no" represents the absence of chronic heart failure and "yes" represents the presence of chronic heart failure.

By analyzing the data, we can identify the possible values of "nr_02" for each target class:

For the target class "no" (absence of chronic heart failure), the possible values of "nr_02" could be:
- "no": This is the obvious value as it represents the absence of premature ventricular contractions in the anamnesis, which aligns with the absence of chronic heart failure.

For the target class "yes" (presence of chronic heart failure), the possible values of "nr_02" could be:
- "yes": This indicates the presence of premature ventricular contractions in the anamnesis, which may be associated with the presence of chronic heart failure.

Based on this analysis, the dictionary capturing the possible values of "nr_02" for each target class would be as follows:

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