Based on prior knowledge, let's analyze the relationship between the feature "day" and the task of whether the client subscribes to a term deposit or not.

Typically, the "day" feature represents the last contact day of the month. It can have values ranging from 1 to 31. 

To analyze the relationship, we can examine the distribution of the "day" values for clients who subscribed to a term deposit (target class "yes") and for clients who did not (target class "no"). Let's generate a dictionary with the relevant details:

```json
{
    "no": [5, 15, 20, 25, 30],
    "yes": [10, 5, 28, 2, 15]
}
```

In this dictionary, the "no" key represents the target class of clients who did not subscribe to a term deposit, and the "yes" key represents the target class of clients who did subscribe to a term deposit. The values associated with each key are five typical "day" values for each target class.

Please note that these values are hypothetical and based on assumptions as the specific dataset or real-world scenario is not provided.