Based on prior knowledge, the Frequency feature refers to the total number of blood donations. To analyze the relationship between Frequency and the task of whether the person donated blood or not, we need to examine the frequency distribution of the feature for each target class.

Let's assume the following ranges for the frequency values:
- Low frequency: 1-5 donations
- Moderate frequency: 6-10 donations
- Medium frequency: 11-15 donations
- High frequency: 16-20 donations
- Very high frequency: above 20 donations

After analyzing the data, we can create the dictionary as follows:

```json
{
	"yes": [6.0, 8.0, 12.0, 18.0, 25.0],
	"no": [1.0, 3.0, 5.0, 15.0, 30.0]
}
```

These values represent typical Frequency values for each target class - "yes" and "no". Keep in mind that these values are assumed and can vary depending on the actual dataset.