This is an R-help list. These are not questions about R. You should
talk to a local statistical expert instead of posting here.
Cheers,
Bert
On Mon, Oct 14, 2013 at 1:23 PM, Lorenzo Isella
lorenzo.ise...@gmail.com wrote:
Dear All,
For a project I am given a set of images. They represent either healthy or
tumoral tissue, but the specific nature of the images does not matter.
I need to train a classifier which is expected to tell me in which category
(let's call it 0 vs 1) each image falls.
I am thinking about a random forest classifier, but I am uncertain about a
couple of (fairly important) points
(1) The size of the images varies, so for instance the number of pixels is
not the same for every image and as a consequence some methodologies (e.g.
the PCA) when applied to these images will lead to results not immediately
comparable. Is trying to blur/flatten the images a good idea to have always
(artificially) the same size (number of pixels) for every image?
(2) Which features do you recommend to associate\calculate for every image?
This is what I will use to train my model upon.
Any suggestion is welcome.
Cheers
Lorenzo
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--
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
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