Based on my prior knowledge, I can analyze the relationship between the feature "previous" and the task of whether the client subscribed to a term deposit or not.

Analyzing the Relationship:
- In general, it is expected that clients who have been contacted multiple times before this campaign and for this specific product are more likely to subscribe to a term deposit.
- However, there might be a threshold beyond which frequent contacts might lead to lower chances of subscribing, as clients may become uninterested or annoyed.
- To determine the appropriate ranges of values for "previous", it would be helpful to analyze the distribution of values and identify any significant patterns or outliers.

Based on this analysis, here is the generated dictionary:

```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 five typical previous values for each target class ('no', 'yes'). The values are presented as floats in lists. However, please note that the values mentioned above are arbitrary and might vary depending on the actual dataset being used.