Based on my prior knowledge, I can analyze the relationship between the feature "duration" and the target variable "Does this client subscribe to a term deposit?".

In general, the duration of the last contact with the client could potentially be a determining factor for whether the client subscribes to a term deposit or not. Clients who had a longer duration of the last contact might have had a more engaging conversation with the bank representative, which could increase their likelihood of subscribing to a term deposit.

With that said, here is the analysis of the relationship between the feature "duration" and the target variable "Does this client subscribe to a term deposit?":

For the "no" class (clients who did not subscribe to a term deposit):
- It is possible to have a range of durations, but typically I would expect the values to be on the lower side.
- Example typical duration values: 10.5, 15.2, 12.3, 18.9, 9.7

For the "yes" class (clients who subscribed to a term deposit):
- Duration values might be comparatively higher, indicating longer conversations with the bank representative.
- Example typical duration values: 45.7, 52.1, 48.9, 50.2, 55.6

Based on this analysis, here is the generated dictionary:

```json
{
	"no": [10.5, 15.2, 12.3, 18.9, 9.7],
	"yes": [45.7, 52.1, 48.9, 50.2, 55.6]
}
```