Based on prior knowledge and understanding of the feature and task, we can analyze the relationship between the feature "nr_01" (Premature atrial contractions in the anamnesis) and the presence of chronic heart failure complications in myocardial infarction (target variable).

To determine if the patient shows chronic heart failure, we need to analyze how the presence or absence of premature atrial contractions in the anamnesis (nr_01) relates to chronic heart failure.

Here's an analysis of the relationship:

- If the value of nr_01 is 'no', it suggests that the patient does not have premature atrial contractions in the anamnesis. In this case, it is more likely that the patient does not show chronic heart failure.
- If the value of nr_01 is 'yes', it suggests that the patient has premature atrial contractions in the anamnesis. In this case, there is a possibility that the patient shows chronic heart failure.

Based on this analysis, we can create a dictionary with the following format:

```json
{
	"no": ["no"],
	"yes": ["yes"]
}
```
Since the feature "nr_01" is a categorical variable with categories 'no' and 'yes', we include these values in the corresponding lists for each target class.