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

First, we need to determine if there is any observable pattern in the occurrences of arrhythmia (nr_11) in the two target classes ("no" for no chronic heart failure and "yes" for chronic heart failure).

To do this, we can examine the frequency of different values of "nr_11" for each target class in the dataset.

Here's a possible analysis:

- For the target class "no" (no chronic heart failure), these are the possible values of "nr_11" and their frequencies:

    - "no": [list of string] (possible values of feature nr_11 for target class no)
    - "yes": [list of string] (possible values of feature nr_11 for target class no)

- For the target class "yes" (chronic heart failure), these are the possible values of "nr_11" and their frequencies:

    - "no": [list of string] (possible values of feature nr_11 for target class yes)
    - "yes": [list of string] (possible values of feature nr_11 for target class yes)

Based on this analysis, we can now create the dictionary as requested:

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

Please note that this is a hypothetical analysis and the actual values will depend on the dataset being analyzed. Also, there might be other values of "nr_11" that are not captured in this analysis if they are hard to predict or infrequent.