Based on my prior knowledge, I can assume that the Frequency feature represents the total number of times a person has donated blood. To analyze the relationship between the Frequency feature and the task of whether the person donated blood or not, I can make the following observations:

1. If the Frequency value is 0, it indicates that the person has never donated blood before. This is likely to be more common in the 'no' class.
2. Individuals who have donated blood multiple times are more likely to have a higher Frequency value. Hence, higher Frequency values may be more common in the 'yes' class.
3. However, there is a possibility that some individuals in the 'yes' class have only donated blood a few times, while others have donated blood many times. Therefore, there may be a range of Frequency values in both classes.

Based on these observations, I can create the following dictionary:

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

In this dictionary, I have included 5 typical Frequency values for each target class. For the 'yes' class, I have included values ranging from 1.0 to 5.0 to represent individuals who have donated blood multiple times. For the 'no' class, I have included values of 0.0 to represent individuals who have never donated blood before.