Based on prior knowledge, the size of the luggage boot (lug_boot) can have an influence on the decision to buy a car. Let's analyze the relationship between the lug_boot feature and the task of rating the decision to buy the car.

Analyzing the relationship between lug_boot and the target variable, the possible scenarios can be:

1. Unacceptable: If the lug_boot is small, it might be considered unacceptable for potential buyers who require more space for luggage.
2. Acceptable: The lug_boot size being medium or big might be considered acceptable by most potential buyers, as it provides sufficient space for luggage.
3. Good: The lug_boot size being medium might be considered good by potential buyers who require a moderate amount of space for luggage.
4. Very Good: The lug_boot size being big might be considered very good by potential buyers who require a large amount of space for luggage.

Based on this analysis, let's create the dictionary:

```json
{
	"unacceptable": ["small"],
	"acceptable": ["med", "big"],
	"good": ["med"],
	"very good": ["big"]
}
```

Note that the dictionary only includes the specific values of lug_boot that are most likely to correspond to each target class. Any other values are not included in the dictionary, assuming they have less influence on the target variable or their relationship is hard to predict.