```json
{
	"yes": [0.085, 0.2, 0.375, 0.64, 0.8],
	"no": [0.085, 0.2, 0.375, 0.64, 0.8]
}
```

Based on the given feature description, the DiabetesPedigreeFunction is a numeric variable that measures the genetic influence or hereditary risk of diabetes. To analyze its relationship with the task of determining if a person has diabetes or not, we can assume that a higher value of the DiabetesPedigreeFunction indicates a higher genetic risk of diabetes.

To generate the dictionary, I assumed 5 typical values for each target class, 'yes' and 'no', based on prior knowledge. I used the same values for both target classes since the description does not provide any information distinguishing the DiabetesPedigreeFunction values for each class. These values are:

- 'yes': [0.085, 0.2, 0.375, 0.64, 0.8]
- 'no': [0.085, 0.2, 0.375, 0.64, 0.8]

Note that these are just example values and the actual values might differ based on the dataset and the specific relationship between the feature and the target variable.