Based on prior knowledge, the feature TIME_B_S represents the time elapsed from the beginning of the attack of Coronary Heart Disease (CHD) to the hospital. To analyze the relationship between this feature and the presence of chronic heart failure as a myocardial infarction complication, we can compare the distribution of TIME_B_S values for the target classes "yes" and "no".

Here is the analysis:

- "2-4 hours": It is likely that patients who reach the hospital within 2-4 hours of the attack have a lower risk of developing chronic heart failure.

- "less than 2 hours": Patients who reach the hospital within 2 hours of the attack may have better outcomes and a lower chance of developing chronic heart failure.

- "4-6 hours": Patients who arrive at the hospital within 4-6 hours of the attack may have a moderate risk of developing chronic heart failure.

- "6-8 hours": Patients who take 6-8 hours to reach the hospital may have an increased risk of developing chronic heart failure compared to those who arrive earlier.

- "8-12 hours": Patients who reach the hospital between 8-12 hours may have an even higher risk of developing chronic heart failure.

- "more than 3 days", "more than 2 days", "12-24 hours", and "more than 1 day": It is difficult to predict the relationship between these categories and the risk of chronic heart failure based on the given information.

Based on the above analysis, we can create a dictionary as follows:

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

Please note that the final dictionary is based on assumptions and limited information. It is recommended to perform further analysis or consult domain experts for a more accurate assessment.