Variance maximization is a statistical technique used to transform data in a way that emphasizes the most significant features or components, often employed in dimensionality reduction methods like Principal Component Analysis (PCA). By maximizing the variance, this approach ensures that the transformed data retains the most informative aspects, making it easier to identify patterns and insights.

Variance Maximization

Variance maximization

statistical technique

transform data

significant features

dimensionality reduction methods

Principal Component Analysis (PCA) is a dimensionality reduction technique that transforms a dataset into a set of orthogonal components ordered by the amount of variance they capture. It is widely used for feature extraction, noise reduction, and data visualization, especially in high-dimensional datasets.

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