Based on prior knowledge, the feature "previous" represents the number of contacts performed before this campaign and for this client. To analyze the relationship between the "previous" feature and the target variable (whether the client subscribes to a term deposit or not), we can create two lists of float values for the feature "previous" based on the target classes "no" and "yes".

Here is the dictionary with the required format:

```json
{
	"no": [0.0, 1.0, 2.0, 3.0, 4.0],
	"yes": [0.0, 1.0, 2.0, 3.0, 4.0]
}
```

This dictionary includes 5 typical values (0.0, 1.0, 2.0, 3.0, and 4.0) for each target class ("no" and "yes"). These values represent different possible ranges of the feature "previous" for clients who did not subscribe to a term deposit (class "no") and those who did subscribe to a term deposit (class "yes").