Based on my prior knowledge, I know that frequent premature atrial contractions (n_r_ecg_p_02) can be an indication of an abnormal heart rhythm. Chronic heart failure is a condition where the heart is unable to pump blood properly and it can be caused by various factors including abnormal heart rhythms.

To analyze the relationship between the feature n_r_ecg_p_02 and the presence of chronic heart failure, I would first examine the data and observe the distribution of the feature values for different target classes.

Based on the analysis, I would create a dictionary with the possible values of the feature n_r_ecg_p_02 for each target class. The values for the target class "no" would represent the feature values observed in patients without chronic heart failure, and the values for the target class "yes" would represent the feature values observed in patients with chronic heart failure.

Here's the dictionary based on the analysis:

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

Note: The feature n_r_ecg_p_02 has two possible values - "no" and "yes". However, it is important to note that this analysis is based on limited information. To make a more accurate determination, it may be necessary to consider other features and perform statistical analysis or machine learning algorithms.