Based on the given feature, "Presence of chronic Heart failure in the anamnesis", and the task of determining if the patient shows chronic heart failure, we need to analyze the relationship between this feature and the target variable.

In this case, the feature ZSN_A represents the stage of chronic heart failure, with the following categories: ['there is no chronic heart failure', 'I stage', 'IIА stage', 'IIB stage'].

To analyze the relationship between ZSN_A and the presence of chronic heart failure, we can look at the data and observe which ZSN_A values are associated with chronic heart failure (class "yes") and which are associated with the absence of chronic heart failure (class "no").

Here's a dictionary representing the relationship between the feature ZSN_A and the presence of chronic heart failure:

```json
{
	"no": ["there is no chronic heart failure"], 
	"yes": ["I stage", "IIА stage", "IIB stage"]
}
```

Based on the analysis, the ZSN_A values associated with chronic heart failure ("yes") are "I stage", "IIА stage", and "IIB stage", while the ZSN_A value associated with the absence of chronic heart failure ("no") is "there is no chronic heart failure".

Note: In cases where there are no instances of a certain ZSN_A value for a target class, it is not necessary to include that value in the dictionary.