Based on prior knowledge and analysis, the relationship between the feature "day" (last contact day of the month) and the task of whether the client subscribes to a term deposit can be determined.

Typically, it is difficult to derive a specific range of values for day without additional context or domain knowledge. However, we can present a general analysis based on the provided information.

```json
{
	"no": [1.0, 2.0, 3.0, 4.0, 5.0],      
	"yes": [15.0, 20.0, 25.0, 27.0, 30.0]  
}
```

This dictionary represents the possible values of the feature "day" for each target class. The values are presented as floats in lists.
For the "no" class, the typical day values can be 1.0, 2.0, 3.0, 4.0, and 5.0. For the "yes" class, the typical day values can be 15.0, 20.0, 25.0, 27.0, and 30.0.

Please note that these values are hypothetical and may not accurately represent the relationship between the feature "day" and the target variable without further analysis or domain-specific insights.