When we excitedly tell people that the new version of Knowledge Leaps incorporates k-fold validation, their eyes glaze over. When we tell people about the benefits of this feature, we usually get the opposite response.
In simple terms, k-fold validation is like having a team of 10 pHDs working on your data, independently and simultaneously. The application doesn't produce just one prediction, it makes 10 which are all independent of one another. This approach outputs more general models, these are closer to a rule of thumb and are consequently useful in more contexts. Another step toward human-centered analytics without the human bias.
