Based on prior knowledge, the ST_Slope feature can indicate the presence of a heart disease. Here's the analysis of the relationship between the feature and the task:

If the coronary angiography of a patient shows a heart disease, it is likely that the ST_Slope will be "Down" or "Flat". This is because a downward or flat ST_Slope may indicate abnormal electrical activity in the heart during exercise, which can be a sign of a heart disease.

If the coronary angiography does not show a heart disease, the ST_Slope can be any value ("Up", "Flat", or "Down"). However, it is important to note that if the ST_Slope is "Up", it is less likely to be associated with a heart disease compared to "Down" or "Flat".

Based on this analysis, the dictionary with the possible values of feature ST_Slope for each target class is as follows:

```json
{
	"no": ["Up", "Flat", "Down"],
	"yes": ["Flat", "Down"]
}
```

Note: The "Up" value is included in the "no" class because it is still a possible value, but it is less likely to be associated with a heart disease.