To analyze the relationship between the feature 'day' and the task of whether the client subscribes to a term deposit, we can examine the distribution of 'day' values for each target class ('no' and 'yes').

Based on prior knowledge, the feature 'day' represents the last contact day of the month. Given that a month typically has 28-31 days, we can assume that reasonable ranges for the feature 'day' would be 1 to 31.

Analyzing the data, we can generate the dictionary as follows:

```json
{
	"no": [2.0, 5.0, 8.0, 15.0, 28.0],
	"yes": [7.0, 10.0, 17.0, 20.0, 25.0]
}
```

In the 'no' target class, the possible values of the feature 'day' could be [2.0, 5.0, 8.0, 15.0, 28.0]. In the 'yes' target class, the possible values of the feature 'day' could be [7.0, 10.0, 17.0, 20.0, 25.0].

Please note that these values are just examples and may vary depending on the specific dataset and analysis.