Based on prior knowledge, we can analyze the relationship between the feature "TIKL_S_n" and the task of determining whether the patient shows chronic heart failure.

To analyze the relationship, we can look at the distribution of the "TIKL_S_n" feature for the two target classes: "no" (no chronic heart failure) and "yes" (chronic heart failure).

Here is the dictionary with the possible values of the "TIKL_S_n" feature for each target class:

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

Explanation:
- For the target class "no" (no chronic heart failure), the only possible value of the "TIKL_S_n" feature is "no".
- For the target class "yes" (chronic heart failure), the possible values of the "TIKL_S_n" feature are "no" and "yes".

Note: We are assuming that there are no other possible values for the "TIKL_S_n" feature based on the given feature description. If there are additional values, they can be included in the dictionary accordingly.