Based on my prior knowledge, I can analyze the relationship between the feature "K_SH_POST" and the task of determining whether the patient shows chronic heart failure.

To analyze this relationship, I would first compare the values of the feature "K_SH_POST" for patients who have chronic heart failure (target class yes) and those who do not have chronic heart failure (target class no). By examining the distributions of "K_SH_POST" values within each target class, I can determine if there is any correlation between the presence of cardiogenic shock at the time of admission to the intensive care unit and the likelihood of chronic heart failure.

Let's generate the dictionary:

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

Based on the analysis, it appears that patients who do not have chronic heart failure (target class no) do not show any presence of cardiogenic shock at the time of admission ("K_SH_POST" value: "no"). On the other hand, patients who have chronic heart failure (target class yes) can have either a presence ("K_SH_POST" value: "yes") or absence ("K_SH_POST" value: "no") of cardiogenic shock at the time of admission.

Please note that this analysis is based on a hypothetical scenario and the accuracy of the results may vary depending on the actual dataset and context.