Based on prior knowledge and analysis, the relationship between the "lug_boot" feature and the target variable ("How would you rate the decision to buy this car?") can be analyzed as follows:

- Unacceptable: It is possible that cars with a small sized luggage boot (lug_boot = 'small') may be rated as unacceptable. Cars with medium sized (lug_boot = 'med') or big sized luggage boots (lug_boot = 'big') may also be rated as unacceptable, but this relationship is less clear and may vary.
- Acceptable: Cars with medium sized luggage boots (lug_boot = 'med') may be rated as acceptable. However, cars with small or big sized luggage boots (lug_boot = 'small' or lug_boot = 'big') may also be rated as acceptable to some extent.
- Good: It is likely that cars with big sized luggage boots (lug_boot = 'big') may be rated as good. There is less certainty about the relationship between lug_boot and the "good" rating for cars with medium or small sized luggage boots (lug_boot = 'med' or lug_boot = 'small').
- Very Good: It is uncertain how the lug_boot feature relates to the "very good" rating. It is possible that cars with any size of luggage boots (lug_boot = 'small', lug_boot = 'med', or lug_boot = 'big') may receive the "very good" rating.

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

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

Note: The list of each target class is not empty in the generated dictionary, as per the requirement.