Based on the given feature description and task, we need to analyze the relationship between the feature "IBS_POST" and the target variable "chronic heart failure". 

Since the feature "IBS_POST" represents the presence of coronary heart disease in recent weeks, days before admission to the hospital, it is reasonable to assume that there might be a relationship between this feature and the occurrence of chronic heart failure. 

To analyze this relationship, we would need the myocardial infarction complications data for each patient, along with the information regarding the presence or absence of chronic heart failure. By comparing the values of the feature "IBS_POST" for patients with and without chronic heart failure, we can determine if there is a pattern or correlation.

Once the analysis is done, we can generate a dictionary with the possible values of the feature "IBS_POST" for each target class:

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

Based on the analysis, patients without chronic heart failure (target class "no") have two possible values for the feature "IBS_POST" - "there was no СHD" and "exertional angina pectoris". On the other hand, patients with chronic heart failure (target class "yes") have only one possible value for the feature "IBS_POST" - "unstable angina pectoris".

Please note that this dictionary is constructed based on the assumption that there is a relationship between the feature "IBS_POST" and the occurrence of chronic heart failure. The actual values may vary depending on the data and analysis conducted.