… what is it?
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Weighted local polynomial regression is a way to predict what will happen in future based on data from the past. It uses data from the past to fit a curve or line to the data, but it also takes into account how close the data points are to each other, by assigning weights to each of the data points. The closer the data points are, the higher the weight given to the data point. This helps the prediction be more accurate.
Simply put, it is to use information it already has to complete something. This is used in some AIs like DALL-E that expand an image. It uses the data it’s already got and tries to predict what is, or could, be in the outer bounds of the image.
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