How To Correctly Validate Machine Learning Models

Description
Model accuracy calculation is an essential part of all machine learning projects, but a lot of data science tools make it very difficult to evaluate how accuracy the model really is. A lot of the time, tools will only validate the model selection, not what goes on surrounding selection. Or worse than that, they don't support techniques like cross-validation.

This paper talks about the 4 principal components for the correct validation of machine learning models and how RapidMiner Studio correctly validates their models.

*Originally shared on rapidminer.com*