METHODS FOR FILTERING DATA AND FILLING IN MISSING DATA USING NONLINEAR INFERENCE

摘要

The present invention is directed to a method for inferring/estimating missing values in a data matrix d(q, r) having a plurality of rows and columns comprises the steps of: organizing the columns of the data matrix d(q, r) into affinity folders of columns with similar data profile, organizing the rows of the data matrix d(q, r) into affinity folders of rows with similar data profile, forming a graph Q of augmented rows and a graph R of augmented columns by similarity or correlation of common entries; and expanding the data matrix d(q, r) in terms of an orthogonal basis of a graph Q×R to infer/estimate the missing values in said data matrix d(q, r).on the diffusion geometry coordinates.