Based on prior knowledge, we can analyze the relationship between the feature 'INF_ANAM' (Quantity of myocardial infarctions in the anamnesis) and the occurrence of chronic heart failure.

The feature INF_ANAM represents the number of myocardial infarctions in the patient's medical history. In this case, we need to determine whether the patient has chronic heart failure. It is likely that patients with a higher number of myocardial infarctions in the anamnesis have a higher likelihood of developing chronic heart failure.

To analyze the relationship, we can look at the proportion of patients with chronic heart failure (yes) and without chronic heart failure (no) across different categories of INF_ANAM. This will help us assess how the feature relates to the target variable.

Based on the analysis, let's create the dictionary:

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

In this case, patients with zero, one, or two myocardial infarctions in the anamnesis are more likely to not have chronic heart failure. On the other hand, patients with three or more myocardial infarctions are more likely to have chronic heart failure.

It is important to note that this analysis is based on prior knowledge and assumptions. Further analysis using statistical methods and a larger dataset would provide a more accurate understanding of the relationship between INF_ANAM and chronic heart failure.