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

Analysis:

In general, the number of times a person has been pregnant may have an impact on the likelihood of developing diabetes. However, it is important to note that other factors such as age, genetics, and lifestyle choices also play a significant role in determining the likelihood of developing diabetes.

Usually, the number of pregnancies for individuals without diabetes tends to be lower compared to those with diabetes. However, there is no specific range of values for the number of pregnancies that guarantees the presence or absence of diabetes. Therefore, it is difficult to establish exact thresholds or ranges for this feature, as individual cases can vary significantly.

Dictionary:

Based on the analysis, we can create a dictionary as follows:

```json
{
	"yes": [1.0, 3.0, 6.0, 8.0, 10.0],
	"no": [0.0, 2.0, 4.0, 5.0, 7.0]
}
```

Please note that these values are just examples and may not be representative of the entire dataset. It is essential to analyze a specific dataset to determine the actual values and their distribution.