How is computed the accuracy for Suggest Features in circular projection ? #5284
Description
Hello,
The function Suggest Features in Linear Projection is very interesting. Can you explain how the combination of features are ranked please ? In the doc, it is mentioned that "This feature scores attributes by average classification accuracy and returns the top scoring attributes with a simultaneous visualization update", but the way the accuracy is computed is not clear (https://orange3.readthedocs.io/projects/orange-visual-programming/en/latest/widgets/visualize/linearprojection.html). Is it univariate accuracy of independent feature averaged across the combination of the selected features (for example 3 in the example of the doc)? Or is it a multivariate accuracy of a model made with theses features ? It would be very usefull to know since this tool is very usefull in my field (radiomics). Is the accuracy coputed by class or on the whole dataset ?
Thank you very much in advance.