Eigenvectors
In linear algebra, eigenvectors are the non-zero vectors that only change by a scalar factor when a linear transformation is applied to them. In data science, eigenvectors are used in principal component analysis (PCA) to reduce the dimensionality of a dataset while retaining as much of the original variation as possible. Eigenvectors are also used in machine learning algorithms such as clustering and classification. They are particularly useful in image and signal processing, where they can be used to extract features from the data.
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