Based on my prior knowledge, I will analyze the relationship between the feature "SkinThickness" and the task of determining if a person has diabetes or not.

The "SkinThickness" is a numeric variable that represents the Triceps skin fold thickness in millimeters. Typically, a higher skin fold thickness indicates a higher probability of having diabetes. However, it is important to note that the relationship between "SkinThickness" and diabetes is not deterministic and can vary from person to person.

Analyzing the data, I will identify some typical SkinThickness values for each target class ('yes' and 'no'). Here is the dictionary with the analysis results:

```json
{
	"yes": [35.0, 40.0, 45.0, 50.0, 55.0], 
	"no": [15.0, 20.0, 25.0, 30.0, 32.0]
}
```

In this analysis, the typical SkinThickness values for the "yes" class (people with diabetes) could be 35.0, 40.0, 45.0, 50.0, and 55.0. Conversely, the typical SkinThickness values for the "no" class (people without diabetes) could be 15.0, 20.0, 25.0, 30.0, and 32.0.

Please note that these values are just examples and should be interpreted as possible ranges rather than strict thresholds. The actual range of SkinThickness values for each target class may vary depending on the dataset and specific characteristics of the population.