Based on the feature description, the feature "ritm_ecg_p_01" represents the ECG rhythm at the time of admission to the hospital. It is a categorical variable with two categories: 'yes' and 'no'. 

To determine if it shows chronic heart failure, we need to analyze the relationship between this feature and the target variable (myocardial infarction complications data).

To perform this analysis, we can group the patients based on their myocardial infarction complications data, and then examine the distribution of "ritm_ecg_p_01" values within each group.

Let's assume we have a dataset with the following information:

| ritm_ecg_p_01 | Myocardial Infarction Complications |
|--------------|------------------------------------|
| yes          | yes                                |
| yes          | no                                 |
| no           | yes                                |
| yes          | yes                                |
| yes          | no                                 |
| no           | no                                 |
| no           | no                                 |
| no           | no                                 |
| yes          | yes                                |
| no           | yes                                |

From this dataset, we can see that:
- When the myocardial infarction complications are "yes", there are both "yes" and "no" values for "ritm_ecg_p_01".
- When the myocardial infarction complications are "no", there are only "no" values for "ritm_ecg_p_01".

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

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

Please note that the dictionary includes all possible values for each target class. The "no" class only has the "no" value for "ritm_ecg_p_01". The "yes" class has both "yes" and "no" values for "ritm_ecg_p_01".

The purpose of including the "no" value for the "yes" class is to indicate that some patients with myocardial infarction complications also had "no" values for "ritm_ecg_p_01".

Please note that this analysis is based on the assumption made for the dataset provided. The actual analysis may vary depending on the dataset used.