ANALYSIS OF THE EFFICIENCY OF DIMENSIONAL REDUCTION METHODS IN IMAGE PROCESSING
It is proposed to use the singular value decomposition of matrices to reduce the feature space of images. The study of the influence of the degree of compressibility of images on various recognition metrics based on random forest algorithms has been carried out. It is shown that for compressed reductions, high values of the oob metric can be obtained, but additional processing is required to obtain high values of the accuracy metric.