Based on my prior knowledge, the feature "SVT_POST" represents paroxysms of supraventricular tachycardia at the time of admission to the intensive care unit. The task is to determine whether the patient shows chronic heart failure based on the myocardial infarction complications data.

To analyze the relationship between the feature "SVT_POST" and chronic heart failure, we can examine the distribution of the feature values for each target class. By comparing the distribution of "SVT_POST" values for patients with and without chronic heart failure, we can determine if there is a significant association between the feature and the target variable.

Based on this analysis, we can create a dictionary as follows:

```json
{
	"no": ["no"],  
	"yes": ["yes"]
}
```

Here, the value for the "no" class is ["no"], indicating that patients without chronic heart failure have the only possible value of "no" for the feature "SVT_POST." The value for the "yes" class is ["yes"], indicating that patients with chronic heart failure have the only possible value of "yes" for the feature "SVT_POST."

Since the feature "SVT_POST" is categorical and has only two possible values, we don't need to include any other values in the dictionary.