Based on prior knowledge, we need to analyze the relationship between the feature "SIM_GIPERT" (symptomatic hypertension) and the target variable "chronic heart failure" to determine if it shows a correlation.

To conduct this analysis, we would need a dataset containing the "SIM_GIPERT" feature, the target variable "chronic heart failure," and patient data. Without the dataset, we can only make assumptions based on general knowledge.

Assuming that symptomatic hypertension is a known risk factor for chronic heart failure, we can hypothesize that individuals with a value of "yes" for the "SIM_GIPERT" feature are more likely to have chronic heart failure compared to those with a value of "no."

Based on this hypothesis, we can generate the requested dictionary:

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

In this case, since "SIM_GIPERT" is a categorical variable with only two categories ("no" and "yes"), we include those values in the respective target class lists.

Please note that without the actual dataset to analyze, this is a hypothetical analysis based on prior knowledge and assumptions. The accuracy of the analysis would depend on the availability of data and the specific relationship between the feature and the target variable in the dataset.