Based on prior knowledge, there is a potential relationship between the feature "n_r_ecg_p_02" and the task of determining whether the myocardial infarction complications data of the patient show chronic heart failure.

To analyze this relationship, we can examine the distribution of values for the feature in each target class.

Here is the dictionary with the requested format:

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

Since the feature "n_r_ecg_p_02" is a categorical variable with only two categories ('no' and 'yes'), the possible values for each target class are straightforward. The target class "no" corresponds to the value "no" for the feature, and the target class "yes" corresponds to the value "yes" for the feature.

In this case, the dictionary shows that the possible values of the feature "n_r_ecg_p_02" for the target class "no" are ['no'], and the possible values for the target class "yes" are ['yes'].