Based on my prior knowledge, high levels of serum cholesterol are often associated with an increased risk of heart disease. However, it's important to note that high cholesterol alone does not confirm the presence of heart disease as there can be other factors involved.

To analyze the relationship between cholesterol levels and the presence of heart disease, we need access to data containing both the cholesterol values and corresponding labels indicating the presence or absence of heart disease. With this data, we can identify typical cholesterol values for each target class.

Considering this limitation, I will assume the following typical ranges for cholesterol levels based on general medical guidelines:

- Low cholesterol levels: below 200 mg/dl
- Normal cholesterol levels: 200-239 mg/dl
- Borderline high cholesterol levels: 240-259 mg/dl
- High cholesterol levels: 260-349 mg/dl
- Very high cholesterol levels: 350 mg/dl and above

Without the specific data, it is not possible to provide detailed values for the 'no' and 'yes' target classes. However, I can provide a dictionary template with the typical cholesterol ranges mentioned above:

```json
{
    "no": [180.0, 190.0, 210.0, 220.0, 230.0],
    "yes": [260.0, 270.0, 280.0, 290.0, 300.0]
}
```

Please note that these values are general approximations and should be validated with the actual dataset in order to provide accurate information.