Based on prior knowledge, there is no direct relationship between gender (feature SEX) and the presence of chronic heart failure. The risk of developing chronic heart failure can be influenced by various factors such as age, family history, medical history, lifestyle choices, and comorbidities. Therefore, it is unlikely that the feature SEX alone can determine the presence of chronic heart failure.

However, in order to create the dictionary as requested, I will analyze the data and find the possible values of feature SEX for each target class.

Let's assume we have a dataset with the target variable indicating whether there is chronic heart failure (yes or no) and the feature SEX. We can analyze the distribution of SEX values for each target class.

For example, let's say we have the following dataset:

| SEX    | Chronic Heart Failure |
|--------|-----------------------|
| male   | yes                   |
| female | no                    |
| male   | yes                   |
| female | yes                   |
| male   | no                    |
| female | no                    |
| male   | no                    |

Based on this dataset, the dictionary would be:

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

Please note that this is just an example to demonstrate how the dictionary would look like. In practice, you would need to analyze the actual dataset to determine the possible values for each target class.