Based on prior knowledge, the feature "n_r_ecg_p_05" represents the presence or absence of paroxysms of atrial fibrillation on ECG at the time of admission to the hospital. To analyze the relationship between this feature and the presence of chronic heart failure, we need to inspect the values of this feature for both classes - "no" and "yes" for chronic heart failure.

Here is the analysis of the relationship:

- For patients without chronic heart failure ("no" class), the possible values of the feature "n_r_ecg_p_05" can be:
   - "no" (indicating no paroxysms of atrial fibrillation on ECG at the time of admission to the hospital)

- For patients with chronic heart failure ("yes" class), the possible values of the feature "n_r_ecg_p_05" can be:
   - "no" (indicating no paroxysms of atrial fibrillation on ECG at the time of admission to the hospital)
   - "yes" (indicating the presence of paroxysms of atrial fibrillation on ECG at the time of admission to the hospital)

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

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

In this dictionary, the "no" key corresponds to the "no" class, and its value is a list containing the possible values of the feature "n_r_ecg_p_05" for patients without chronic heart failure. Similarly, the "yes" key corresponds to the "yes" class, and its value is a list containing the possible values of the feature "n_r_ecg_p_05" for patients with chronic heart failure.