Data fitting is the process of finding a mathematical function or model that closely approximates a set of data points. This process often involves determining the parameters of the model to minimize the difference between the observed data and the values predicted by the model. Data fitting is essential for extracting meaningful insights from data, particularly when dealing with approximations and the projection of data onto subspaces.
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