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Results tagged with pca
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user 70337
Principal component analysis, a technique for dimensionality reduction.
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Is it OK to try to find the best PCA k parameter as we do with other hyperparameters?
Principal Component Analysis (PCA) is used to reduce n-dimensional data to k-dimensional data to speed things up in machine learning. … After PCA is applied, one can check how much of the variance of the original dataset remains in the resulting dataset. A common goal is keeping variance between 90% and 99%. …
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