Exploring Feature Weights using R and Azure Machine Learning Studio

Developer Support March 1, 2019 Mar 1, 2019 03/1/19

I find that machine learning experiment’s results are always interesting and somewhat unexpected in certain cases. On this comparison, the feature ranking results of PFI are often different from the feature selection statistics that are utilized before a model is created. This is useful in many cases, especially when training “black-box” models where it is difficult to explain how the model characterizes the relationship between the features and the target variable.