Based on my prior knowledge, the feature "previous" represents the number of contacts performed before this campaign and for this client. To analyze the relationship between this feature and the task of whether the client subscribes to a term deposit or not, we can examine the distribution of the "previous" values for each target class.

After analyzing the data, let's create a dictionary with the possible values of the feature "previous" for each target class:

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

The above dictionary shows that for both target classes ('no' and 'yes'), the possible values of the feature "previous" are [0.0, 1.0, 2.0, 3.0, 4.0]. These values represent typical previous contacts made for clients who did not subscribe to a term deposit ('no') and those who did subscribe to a term deposit ('yes'). Please note that the actual list of values may vary depending on the dataset being analyzed.