Based on prior knowledge, we can analyze the relationship between the Glucose feature and the task of determining whether a person has diabetes or not.

Typically, high glucose levels are associated with diabetes. Therefore, we can assume that higher values of glucose would indicate a higher likelihood of having diabetes. On the other hand, lower glucose values are usually associated with non-diabetic individuals.

To create the dictionary with the required format, we will assume that values above 200 mg/dL indicate diabetes, and values below 100 mg/dL indicate non-diabetic individuals. We will include 5 typical glucose values for each target class ('yes' and 'no').

```json
{
	"yes": [201.0, 215.0, 230.0, 245.0, 250.0],
	"no": [75.0, 82.0, 95.0, 99.0, 105.0]
}
```

Please note that these values are just examples and may not represent actual glucose levels for the corresponding target classes. They are provided based on the assumption that higher values indicate diabetes and lower values indicate non-diabetic individuals. The actual ranges of glucose values for the target classes should be determined through data analysis and domain knowledge.