To analyze the relationship between the feature "SEX" and the target variable of chronic heart failure in myocardial infarction complications data, we can start by examining the distribution of SEX among patients with and without chronic heart failure.

By observing the data, we can create a dictionary with the values of SEX for each target class:

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

Since SEX is a binary variable with only two categories (male and female), and we have no prior knowledge suggesting that one gender has a higher likelihood of chronic heart failure, both classes have the same set of possible SEX values.

Therefore, we include the values "male" and "female" in both the "no" and "yes" keys of the dictionary.