Based on prior knowledge, we can analyze the relationship between the feature "K_SH_POST" and the target variable "chronic heart failure". 

To determine whether the myocardial infraction complications data show chronic heart failure, we need to assess if patients with cardiogenic shock at the time of admission to the intensive care unit (K_SH_POST = "yes") are more likely to have chronic heart failure compared to patients without cardiogenic shock (K_SH_POST = "no").

To create the dictionary, we need to identify the possible values of the feature "K_SH_POST" for each target class. Assuming we have the following data:

| K_SH_POST | Chronic Heart Failure |
|-----------|----------------------|
| no        | Yes                  |
| no        | No                   |
| yes       | Yes                  |
| yes       | Yes                  |
| no        | No                   |

We can create the following dictionary:

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

This indicates that for patients with chronic heart failure, the only value of "K_SH_POST" observed is "yes", while for patients without chronic heart failure, the only value of "K_SH_POST" observed is "no".