Based on my prior knowledge:

- If the number of previous contacts is higher, it might indicate that the client is more interested in the term deposit, as they have already shown some level of engagement.
- On the other hand, if the number of previous contacts is lower, it might indicate that the client is less interested or unresponsive to the term deposit offer.

With these assumptions in mind, I will analyze the relationship between the feature "previous" and the target variable "Does this client subscribe to a term deposit?".

First, I will extract the values of the "previous" feature for both target classes, "no" and "yes". Then, I will identify typical values for each target class to include in the dictionary.

Here is the analysis and resulting dictionary:

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

In this case, I assumed that the possible values of the "previous" feature are represented as floats.