Based on the given feature description, the feature "n_r_ecg_p_04" represents the presence or absence of frequent premature ventricular contractions (PVCs) on an electrocardiogram (ECG) at the time of admission to the hospital. The feature is a categorical variable with two possible categories: 'yes' and 'no'.

To analyze the relationship between this feature and the task of determining if the myocardial infarction complications data of the patient show chronic heart failure, we can examine the patterns in the target variable for each category of the feature.

Here is the analysis:

- If the patient has chronic heart failure, it is possible that they may have frequent premature ventricular contractions (PVCs) on the ECG at the time of admission. Therefore, the category 'yes' of the feature could be indicative of chronic heart failure.

- On the other hand, if the patient does not have chronic heart failure, they may not have frequent premature ventricular contractions (PVCs) on the ECG at the time of admission. Therefore, the category 'no' of the feature could be indicative of the absence of chronic heart failure.

Based on this analysis, we can generate the following dictionary:

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

In this case, the list of the possible values of the feature for the target class "no" is ["no"], and for the target class "yes" is ["yes"]. Since the feature is a binary categorical variable, there is only one possible value for each target class.