Based on the given feature "housing, has housing loan?", we can analyze its relationship with the target variable "Does this client subscribe to a term deposit?".

Analyzing the relationship between the feature and target:
- If the client has a housing loan, it is possible that they may have financial obligations and may be less likely to subscribe to a term deposit.
- On the other hand, if the client does not have a housing loan, it indicates they may have more disposable income and may be more likely to subscribe to a term deposit.

Based on this analysis, the possible values of the feature "housing" for each target class are as follows:

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

In this case, we have considered that the possible values for the feature "housing" are only 'yes' and 'no'. The target class "no" has the value "no" for the feature "housing", indicating that clients who do not have a housing loan are less likely to subscribe to a term deposit. The target class "yes" has the value "yes" for the feature "housing", indicating that clients who have a housing loan are more likely to subscribe to a term deposit.

Please note that this analysis is based on general assumptions and may vary depending on the specific dataset and context.