Based on prior knowledge, a higher number of contacts performed during a campaign may suggest a higher chance of the client subscribing to a term deposit. However, there may be diminishing returns after a certain threshold. 

To conduct the analysis, we need data that contains the values of the "campaign" feature and the corresponding target variable. Without the data, we can only estimate possible values for "campaign" that are typical for each target class.

Assuming the analysis is based on available data, here is an example dictionary showing possible campaign values for the target classes 'no' and 'yes':

```json
{
	"no": [1.0, 2.0, 3.0, 4.0, 5.0],
	"yes": [3.0, 4.0, 5.0, 6.0, 7.0]
}
```

Note that these values are just examples and may not be accurate. The actual values would depend on the data and further analysis.