Based on prior knowledge, diabetes mellitus in the anamnesis (endocr_01) can be a risk factor for chronic heart failure. Therefore, there might be a higher likelihood of chronic heart failure in patients with a positive history of diabetes mellitus.

To analyze the relationship between the feature endocr_01 and the task of determining chronic heart failure, we can examine the distribution of endocr_01 values for each target class (yes and no). By doing so, we can identify any patterns or differences that might exist.

After analyzing the data, we can generate the dictionary with the specific details as follows:

```json
{
	"no": ["no"],
	"yes": ["yes"]
}
```
Since the feature endocr_01 is a categorical variable with categories 'no' and 'yes', we can see that for both target classes, the possible values of endocr_01 are the same as the categories. Therefore, the dictionary shows that for the target class "no," the only possible value of endocr_01 is "no," and for the target class "yes," the only possible value of endocr_01 is "yes."

Please note that the dictionary only includes the possible values for each target class, and since the feature has only two categories, there is no need to exclude any values or create a list with hard-to-predict values.