Classify

Hello,

I have not run across anything with the Classify function that indicates the number of observations for each group must be equivalent. This has been done previously using LDA (ie Altman z-score paper) but I just want to be clear it is not required using this function.

Thanks

[Austin]

To clarify, I want to be sure it is able to weight each of the separate groups based on their size when discriminating between them. Thanks

Answer 1

[Veera Kanmani]

https://www.mathworks.com/videos/an-introduction-to-classification-68891.html

Answer 2

[Kenta]

For example, in Support Vector Machine (SVM), you can specify the weitht of each class by defining some parameters such as cost and prior. I am not sure if my answer can response to what you intended to ask, but I hope it can help you.

If you impose a great penalty if A is classified into B, such inference will not happen a lot. When the number of images (sample) which belong to class A is much greater, many test images might be classified into A. In that case, you can weight each class.

https://jp.mathworks.com/help/stats/fitcecoc.html