Based on prior knowledge, there might not be a direct relationship between a person's gender (feature: SEX) and their likelihood of experiencing chronic heart failure (target: myocardial infarction complications data). However, it is still possible to analyze the relationship between these variables using the given data.

To generate the dictionary, we need to analyze the feature (SEX) for each target class (yes and no) separately.

Let's assume the following data:

| SEX    | Target |
|--------|--------|
| male   | no     |
| female | no     |
| male   | yes    |
| female | yes    |
| male   | no     |
| male   | no     |
| female | yes    |
| female | yes    |
| female | no     |
| male   | yes    |

Based on this data, we can create the following dictionary:

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

Note: The dictionary includes all possible values of the feature SEX for each target class. In this case, both target classes have the same possible values for the feature SEX.