To analyze the relationship between the feature "ant_im" and the presence of chronic heart failure in myocardial infarction complications data, we will examine the distribution of "ant_im" values among the two target classes ("yes" and "no").

Based on the given description, the possible categories for the "ant_im" feature are:
['QRS is like QS-complex', 'QRS has no changes', 'there is no infarct in this location', 'QRS is like QR-complex', 'QRS is like Qr-complex'].

To determine the relationship, we need data samples that include both the "ant_im" values and the corresponding information about chronic heart failure (target variable).

Since we don't have access to such data, we can only provide a frequency analysis of the possible values of "ant_im" for each target class.

Here is the dictionary with the possible "ant_im" values for each target class:

```json
{
	"no": ["QRS is like QS-complex", "QRS has no changes", "there is no infarct in this location", "QRS is like QR-complex", "QRS is like Qr-complex"],
	"yes": ["QRS is like QS-complex", "QRS has no changes", "there is no infarct in this location", "QRS is like QR-complex", "QRS is like Qr-complex"]
}
```
Please note that due to the lack of data, the above dictionary includes all possible "ant_im" values for both "yes" and "no" classes, assuming they could potentially be present. However, it is important to validate the relationship between the feature and the target variable with actual data to confirm any associations.