Based on prior knowledge, the marital status of a client could potentially have an impact on whether they subscribe to a term deposit or not. Let's analyze the relationship between the feature "marital" and the target variable.

To do this, we would need to examine the dataset and determine how the different marital statuses are distributed among the clients who subscribe to a term deposit ("yes" class) and those who do not ("no" class).

Here's the dictionary with possible values of the "marital" feature for each target class:

```json
{
    "no": ["married", "single", "divorced"],  
    "yes": ["married", "single", "divorced"]  
}
```

In this case, all possible values of the "marital" feature are considered for both target classes, as there is no prior knowledge indicating that any specific marital status is more likely to result in subscribing to a term deposit.