Based on prior knowledge, we need to analyze the relationship between the feature "TIKL_S_n" and the target variable "chronic heart failure" to determine whether the patient's myocardial infarction complications data shows chronic heart failure. 

To create the required dictionary, we need to identify the possible values of the feature "TIKL_S_n" for each target class. Let's analyze the possible values:

If the target class is "no" (indicating no chronic heart failure), the feature values could be ['no'].

If the target class is "yes" (indicating chronic heart failure), the feature values could be ['no', 'yes'].

Based on this analysis, we can create the dictionary:

```json
{
	"no": ["no"],
	"yes": ["no", "yes"]
}
```
This indicates that if the patient's myocardial infarction complications data shows chronic heart failure, the possible values for the feature "TIKL_S_n" can be "no" or "yes". Otherwise, if chronic heart failure is not present, the feature value can only be "no".