Based on the given information, it is not clear how the feature "Repetition" relates to the target variable of grain yield. In order to determine the relationship, it would be helpful to have more information about what the feature "Repetition" represents and how it is measured or calculated. Without this additional information, it is not possible to provide an accurate analysis of the relationship between "Repetition" and grain yield.

However, if we assume that "Repetition" refers to the number of times a particular experiment or measurement is repeated for each soybean cultivar, we can make some general assumptions about its relationship with grain yield.

Assuming that more repetitions of an experiment lead to a more accurate and reliable measurement of grain yield, we can hypothesize that a high value of "Repetition" may be associated with a high grain yield. Conversely, a low value of "Repetition" may be associated with a low grain yield.

Based on this hypothesis, we can create a dictionary as follows:

```json
{
	"low": [1.0, 2.0, 3.0, 4.0, 5.0],
	"high": [11.0, 12.0, 13.0, 14.0, 15.0]
}
```

Please note that these values are just examples and should not be interpreted as actual data. The values provided in the dictionary represent five typical values of "Repetition" for each target class, "low" and "high".