Based on prior knowledge, we can analyze the relationship between the feature "Observing of arrhythmia in the anamnesis" (feature nr_11) and the presence of chronic heart failure in the myocardial infarction complications data.

If the feature value is "yes" (Observing of arrhythmia in the anamnesis was recorded), it may indicate a higher likelihood of chronic heart failure. On the other hand, if the feature value is "no" (Observing of arrhythmia in the anamnesis was not recorded), it may suggest a lower likelihood of chronic heart failure.

To create the dictionary, we need to analyze the data and categorize the possible values of feature nr_11 for each target class (yes and no).

Here is the dictionary with the possible values of feature nr_11 for each target class:

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

Note that based on the limited information available, we cannot determine the exact values of feature nr_11 that are hard to predict. Therefore, we have included all possible values (both "no" and "yes") for the target class "yes" in the dictionary.