Based on prior knowledge, we can analyze the relationship between the feature INF_ANAM and the presence of chronic heart failure.

From the feature description, INF_ANAM represents the quantity of myocardial infarctions in the patient's medical history. It is a categorical variable with the following possible categories: 'one', 'zero', 'two', 'three and more'.

To analyze the relationship, we can look at the distribution of INF_ANAM categories for patients with and without chronic heart failure. We'll compare the frequencies of each category for both target classes.

Since the task is to determine if the patient shows chronic heart failure or not, we will create a dictionary that lists the possible values of INF_ANAM for each target class.

Based on this analysis, the expected dictionary would look like:

```json
{
    "no": ["one", "zero", "two", "three and more"],
    "yes": ["one", "zero", "two", "three and more"]
}
```
Note that we are including all possible values of INF_ANAM in both target classes. However, if there are certain values that appear to be rare or have no clear relationship with chronic heart failure, they may be excluded from the dictionary. Nonetheless, we want to ensure that the list for each target class is not empty.