Based on prior knowledge, we can analyze the relationship between the feature "nr_03" (Paroxysms of atrial fibrillation in the anamnesis) and the target variable "chronic heart failure".

To determine if the myocardial infarction complications data of the patient shows chronic heart failure, we need to consider the occurrence of paroxysms of atrial fibrillation in the patient's medical history.

Since the feature "nr_03" indicates if the patient has experienced paroxysms of atrial fibrillation in the anamnesis, it can potentially be related to the presence or absence of chronic heart failure.

To create the dictionary, we need to identify the possible values of feature "nr_03" for each target class: "no" and "yes".

Possible values for feature "nr_03" associated with chronic heart failure "no" class could be:

- no (patient does not have a history of paroxysms of atrial fibrillation)

Possible values for feature "nr_03" associated with chronic heart failure "yes" class could be:

- yes (patient has a history of paroxysms of atrial fibrillation)

Based on this analysis, the dictionary would look like:

```json
{
	"no": ["no"],
	"yes": ["yes"]
}
```
The values are presented as strings in lists to match the required format.