Based on prior knowledge, the relationship between the "buying" feature and the decision to buy a car can be analyzed as follows:

- "Very high" buying price: It is likely that the decision to buy a car with a "very high" buying price would be rated as "good" or "very good", as customers who can afford such a high price range are more likely to be satisfied with their purchase.
- "High" buying price: The decision to buy a car with a "high" buying price could be rated as "good" or "acceptable", as customers might expect a certain level of quality and features in this price range.
- "Medium" buying price: The decision to buy a car with a "medium" buying price could be rated as "acceptable" or "good", as customers might have moderate expectations for the price they are paying.
- "Low" buying price: The decision to buy a car with a "low" buying price could be rated as "unacceptable" or "acceptable", as customers might have lower expectations in terms of quality and features due to the lower price range.

Based on this analysis, the dictionary can be created as follows:

```json
{
	"unacceptable": ["low"],
	"acceptable": ["low", "medium"],
	"very good": ["very high"],
	"good": ["high", "medium"]
}
```

Note that for the target class "unacceptable", only the value "low" is included as it is the only buying category deemed as unacceptable. Similarly, for the target class "very good", only the value "very high" is included as it is the buying category most likely to result in a very good rating.