Based on prior knowledge, we can analyze the relationship between the feature "O_L_POST" (Pulmonary edema at the time of admission to intensive care unit) and the presence of chronic heart failure complications in patients with myocardial infarction.

To analyze this relationship, we can examine the distribution of "O_L_POST" values for patients with and without chronic heart failure complications.

Here is a possible approach to analyzing the relationship and creating the dictionary:

1. Gather data on patients with myocardial infarction and the presence or absence of chronic heart failure complications.
2. Subset the data based on the target variable (chronic heart failure complications).
3. For the subset of patients with chronic heart failure complications, record the different values of "O_L_POST" and add them to a list.
4. Repeat step 3 for the subset of patients without chronic heart failure complications.
5. Create the dictionary with the format specified, using the lists generated in steps 3 and 4.

Here is an example of what the dictionary output might look like:

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

Please note that this is a high-level analysis, and the specific values in the dictionary may differ depending on the dataset. The actual values should be determined based on the available data and the relationships observed during the analysis.