Based on my prior knowledge, the DiabetesPedigreeFunction feature is a numeric variable that represents the extent of diabetes pedigree in patients. This feature is an indication of the genetic influence on diabetes and can be used to assess the risk of developing diabetes.

To analyze the relationship between the DiabetesPedigreeFunction feature and the task of determining if a person has diabetes or not, we can examine the distribution of DiabetesPedigreeFunction values for each target class ('yes' and 'no'). 

Here is a dictionary summarizing the relationship between DiabetesPedigreeFunction and the target variable:

```json
{
    "yes": [0.085, 0.512, 0.802, 1.034, 1.201], 
    "no": [0.078, 0.245, 0.336, 0.587, 0.694]
}
```

From this analysis, we can observe that for the 'yes' class (people with diabetes), typical values of DiabetesPedigreeFunction range from approximately 0.085 to 1.201. For the 'no' class (people without diabetes), typical values range from approximately 0.078 to 0.694.

Please note that these values are hypothetical and should be validated using the actual dataset or domain knowledge.