Based on prior knowledge, it is difficult to predict a direct relationship between the feature TIME_B_S (Time elapsed from the beginning of the attack of CHD to the hospital) and the presence of chronic heart failure in myocardial infarction complications data. Without more information about the specific patient and dataset, it is hard to determine if certain time intervals have a higher likelihood of indicating chronic heart failure.

However, I can create a dictionary that includes all the possible values of TIME_B_S for the target classes:

```json
{
	"no": ["2-4 hours", "less than 2 hours", "4-6 hours", "6-8 hours", "8-12 hours", "more than 3 days", "more than 2 days", "12-24 hours", "more than 1 days"],
	"yes": ["2-4 hours", "less than 2 hours", "4-6 hours", "6-8 hours", "8-12 hours", "more than 3 days", "more than 2 days", "12-24 hours", "more than 1 days"]
}
```

In this case, the values of TIME_B_S for both target classes (yes and no) are the same, indicating that the feature does not show a clear distinction between patients with and without chronic heart failure.