Background: Neuroscience, India
My thesis is based on the use of machine learning for some neuroscience data. Since I do not expect the readers to be aware of machine learning details, I have written a high level summary (a few pages) before the literature review which summarizes the basic principles of machine learning (like introducing what is cross-validation, how to measure accuracy, false positives, etc.). The idea was to let the reader gain some high level understanding before diving into the actual literature review so that the reader would be able to better appreciate the work previously done and the knowledge gap.
This part of the thesis is based on my understanding, clubbed with courses on machine learning and generally reading around on the internet. As far as I can see, the ideas are simplified 101 which can be easily found from Wikipedia (such as the page describing confusion matrix) and from online blogs. To summarize, as far as I can see this is borderline common knowledge.
My thesis reviewer has raised a concern with this part saying that I have not cited any sources and I should cite academic sources for these concepts. I don't quite see how that is possible as the concepts I have described are very elementary. Most textbooks that describe these ideas do not cite any papers and I don't even know how I am supposed to find citations for concepts like precision and recall!
Question: is my understanding of "common knowledge" incorrect? How could I reply to this concern/find sources for these introductory concepts?