Orthogonal Signal Correction (OSC) is a statistical technique used primarily in chemometrics and signal processing to enhance the predictive performance of models by removing unwanted variability in the data that is orthogonal (i.e., uncorrelated) to the outcome of interest. The main goal of OSC is to improve the extraction of relevant information from noisy or complex data, particularly in situations where this data is high-dimensional.
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