Based on my prior knowledge, the feature INF_ANAM represents the quantity of myocardial infarctions in the patient's medical history. To analyze how this feature relates to the presence of chronic heart failure, I will examine the frequency of each category in INF_ANAM for both the "yes" and "no" classes of chronic heart failure.

Let's assume we have the following dataset:

| INF_ANAM | Chronic Heart Failure |
|----------|----------------------|
| one      | yes                  |
| one      | no                   |
| one      | yes                  |
| zero     | yes                  |
| two      | no                   |
| zero     | no                   |
| three and more | no              |
| zero     | yes                  |
| two      | yes                  |
| one      | no                   |

For the "yes" class (chronic heart failure), the possible values of INF_ANAM are: 'one', 'zero', 'two'. 

For the "no" class (no chronic heart failure), the possible values of INF_ANAM are: 'one', 'zero', 'two', 'three and more'.

Based on this analysis, we can create the following dictionary:

```json
{
	"no": ["one", "zero", "two", "three and more"],
	"yes": ["one", "zero", "two"]
}
```

This dictionary indicates the possible values of INF_ANAM for each target class (chronic heart failure - yes or no).