Based on my prior knowledge, let's analyze the relationship between the feature "housing" and the task of whether a client subscribes to a term deposit.

To do this, we can examine the distribution of the feature values for each target class.

Here is the analysis:

- For clients who do not subscribe to a term deposit (target class: "no"), the possible values for the "housing" feature could be ['yes', 'no'].

- For clients who do subscribe to a term deposit (target class: "yes"), the possible values for the "housing" feature could also be ['yes', 'no'].

Based on this analysis, we can create the following dictionary:

```json
{
	"no": ["yes", "no"],
	"yes": ["yes", "no"]
}
```

Please note that since the feature "housing" has only two possible values ('yes' and 'no'), there is no value that is hard to predict or missing. Therefore, we included all possible values for each target class.