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 a client subscribes to a term deposit or not, we can examine the distribution of the "previous" values for each target class ("yes" or "no").

Here is the analysis and dictionary for the feature "previous" and the task of term deposit subscription:

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

In the target class "no" (client does not subscribe to a term deposit), typical values for the feature "previous" could be [0.0, 1.0, 2.0, 3.0, 4.0]. Similarly, in the target class "yes" (client subscribes to a term deposit), typical values for the feature "previous" could also be [0.0, 1.0, 2.0, 3.0, 4.0]. 

Please note that these are just example values based on common ranges in similar datasets, and the actual distribution may vary depending on the dataset being analyzed.