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At first, it says the default is independent features.
But in the later explanation of parameters, the default is dependent features (but without default covMat
BTW, I caught a typo
And I have a related question. It seems that one should always estimate (or "know") covMat before using the function? Would it be practical when the number of features is too large, e.g., single cell dataset? And do you think how to take the estimation of covMat into account in the whole clustering-testing procedure instead of assuming covMat is given? Thanks.
The text was updated successfully, but these errors were encountered:
The description in
kmeans_inference_1f
seems not consistent on the page https://yiqunchen.github.io/CADET/reference/kmeans_inference_1f.htmlAt first, it says the default is independent features.
But in the later explanation of parameters, the default is dependent features (but without default
covMat
BTW, I caught a typo
And I have a related question. It seems that one should always estimate (or "know")
covMat
before using the function? Would it be practical when the number of features is too large, e.g., single cell dataset? And do you think how to take the estimation ofcovMat
into account in the whole clustering-testing procedure instead of assumingcovMat
is given? Thanks.The text was updated successfully, but these errors were encountered: