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

Based on the given feature, it seems that the feature "nr_03" represents the presence or absence of paroxysms of atrial fibrillation in the patient's medical history. To determine if there is a relationship between this feature and the occurrence of chronic heart failure, we need to analyze how this feature varies for patients with and without chronic heart failure.

If the feature "nr_03" is categorical with categories ['no', 'yes'], we can infer the following relationships:

- For patients without chronic heart failure (target class "no"), the feature "nr_03" can take the value "no".

- For patients with chronic heart failure (target class "yes"), the feature "nr_03" can take the value "yes".

Since "no" and "yes" are the only possible values for this feature, we can create a dictionary that captures this relationship, where the target class "no" is associated with ["no"] and the target class "yes" is associated with ["yes"].