Based on my prior knowledge, I can analyze the relationship between the "previous" feature and the task of whether the client subscribes to a term deposit.

Analysis:

The "previous" feature represents the number of contacts performed before this campaign and for this client. We can assume that the more contacts a client has had in the past, the higher the chances of them subscribing to a term deposit. Therefore, we can expect a positive relationship between the "previous" feature and the task of subscribing to a term deposit. 

However, it is important to note that there might be a point of diminishing returns, where too many previous contacts might lead to a decrease in the likelihood of subscribing. Additionally, clients who have had no previous contacts might also be more likely to subscribe as they might be intrigued by the new campaign.

With this analysis, let's create the dictionary:

```json
{
	"no": [0.0, 1.0, 2.0, 3.0, 4.0],
	"yes": [1.0, 2.0, 3.0, 4.0, 5.0]
}
```

Note: The values provided are just examples and may not represent the exact distribution of "previous" values for each target class. They are meant to illustrate common scenarios.