Based on your prior knowledge, the Diabetes Pedigree Function (DPF) is a numeric variable that quantifies the family history of diabetes. It is calculated based on the genetic relationship between family members and the age at which they were diagnosed. Higher values of DPF indicate a stronger genetic predisposition to diabetes.

To analyze the relationship between the Diabetes Pedigree Function (DPF) feature and the task of determining whether a person has diabetes or not, we can examine the distribution of DPF values across the two target classes ('yes' and 'no').

Here is the dictionary with the details:

```json
{
	"yes": [0.229, 0.48, 1.127, 1.731, 2.42],
	"no": [0.085, 0.304, 0.435, 0.731, 0.926]
}
```

The above dictionary indicates possible values of the Diabetes Pedigree Function (DPF) feature for each target class. The values provided are just examples and are not exhaustive. For the 'yes' target class, some possible DPF values could be 0.229, 0.48, 1.127, 1.731, and 2.42. On the other hand, for the 'no' target class, some possible DPF values could be 0.085, 0.304, 0.435, 0.731, and 0.926.

Please note that these values are for illustrative purposes and further analysis should be conducted to determine the exact ranges of DPF values for each target class.