Based on the given feature "IBS_POST" and the task of determining if the patient shows chronic heart failure, let's analyze the relationship between the feature and the target.

Since the feature "IBS_POST" represents the categories of coronary heart disease in recent weeks, days before admission to the hospital, we can make some assumptions about its relationship with chronic heart failure.

- "there was no СHD": This category implies that there was no coronary heart disease in recent weeks. It is possible that patients without recent CHD may not show chronic heart failure. So this category might be associated with the target class "no".

- "exertional angina pectoris": This category suggests that there was exertional angina pectoris, which is a symptom of coronary artery disease. Patients with this category might have a higher chance of developing chronic heart failure. So this category might be associated with the target class "yes".

- "unstable angina pectoris": This category represents unstable angina pectoris, which is a more serious form of angina. Patients with this category might have an increased risk of complications, including chronic heart failure. So this category might also be associated with the target class "yes".

Based on this analysis, we can create the following dictionary:

```json
{
	"no": ["there was no СHD"],
	"yes": ["exertional angina pectoris", "unstable angina pectoris"]
}
```

Note: It is important to note that this analysis is based on assumptions and prior knowledge. The actual relationship between the feature and the target can only be determined through detailed analysis of relevant data.