Based on my prior knowledge, analyzing the relationship between the feature "previous" and the task of whether the client subscribes to a term deposit, here are the findings:

The feature "previous" represents the number of contacts performed before this campaign and for this client. It is a numeric variable, so we would expect a positive correlation between the number of previous contacts and the likelihood of the client subscribing to a term deposit. Generally, if a client has been contacted more times in the past, they may be more familiar with the product and have a higher likelihood of subscribing to a term deposit.

To provide a detailed analysis, let's examine typical values for "previous" for each target class ('no' and 'yes'):

For the 'no' class (clients who did not subscribe to a term deposit):
- Previous values may range from 0 to 10.
- Typical values for the 'no' class could be: [0.0, 1.5, 3.0, 5.5, 8.0]

For the 'yes' class (clients who subscribed to a term deposit):
- Previous values may range from 0 to 30.
- Typical values for the 'yes' class could be: [2.0, 7.5, 12.0, 18.5, 27.0]

Based on this analysis, here is the formatted dictionary:

```json
{
	"no": [0.0, 1.5, 3.0, 5.5, 8.0],
	"yes": [2.0, 7.5, 12.0, 18.5, 27.0]
}
```
