Based on my prior knowledge, I can analyze the relationship between the feature "previous" (number of contacts performed before this campaign and for this client) and the target variable "subscription to a term deposit".

One possible analysis could be as follows:
- Clients who have previously been contacted multiple times (higher values of "previous") may be more likely to subscribe to a term deposit, as repeated contacts may have increased their interest.
- On the other hand, clients who have not been contacted previously (lower values of "previous") may be less likely to subscribe as they have had less exposure to the campaign.

Based on this analysis, I will create a dictionary with the requested format:

```json
{
	"no": [0.0, 1.0, 2.0, 3.0, 4.0],
	"yes": [5.0, 6.0, 7.0, 8.0, 9.0]
}
```

For target class "no" (client does not subscribe to a term deposit), some typical previous values could be 0.0, 1.0, 2.0, 3.0, and 4.0.
For target class "yes" (client subscribes to a term deposit), some typical previous values could be 5.0, 6.0, 7.0, 8.0, and 9.0.

Please note that the provided typical values are arbitrary and may vary based on the actual dataset and further analysis.