![]() ![]() spermute(s,3 1 2) However, permute is extremely slow and take the largest ammount of time for computation. In order to save my computational time I am using permute function. Predictor importance estimates by permutation of out-of-bag predictor observations for random forest of regression trees. I have a rather large array 20070010000 points. Based on your location, we recommend that you select. dPermuted = permute(d, ) Ĭaxis() % make the range of intensities better įinal step - how to add in an extra singleton dimensionsįor montage() to do the right thing, we need to permute the array to also include a singleton 3rd dimension (see echo360 recording for an explanation). This MATLAB function returns a vector of out-of-bag, predictor importance estimates by permutation using the random forest of regression trees Mdl. Choose a web site to get translated content where available and see local events and offers. What does this all mean? - conclusion of this detailed look is that the dimensions 2 and 3 in these anatomical images are in an order that makes the montage function not produce nice axial slices. % display a slice (which has 1st and 3rd dims) figure, imagesc ( squeeze ( d (:, 128, :))) ylabel ( 'first dimension of array' ) xlabel ( 'third dimension' ) colormap ( gray ) axis image the desired orientations data dimension ![]()
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