Based on prior knowledge, it is important to understand the relationship between the feature "SEX" and the presence of chronic heart failure (target variable) in order to determine if myocardial infarction complications data shows chronic heart failure.

To analyze this relationship, we need data that includes the "SEX" feature and the information on whether chronic heart failure is present or not. By examining this data, we can determine how different categories of gender are associated with the occurrence of chronic heart failure.

Once we have the data, we can create a dictionary with the possible values of the "SEX" feature for each target class. Here's an example of how the dictionary could be formatted:

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

In this example, both target classes have the same possible values for the "SEX" feature, which are "male" and "female". However, this may vary depending on the actual data and the relationship between the feature and the target.