Principal Component Analysis: Revision history

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    1 December 2024

    • curprev 16:2116:21, 1 December 2024‎ Dendrogram talk contribs‎ 3,829 bytes +3,829‎ 새 문서: '''Principal Component Analysis (PCA)''' is a statistical technique used for dimensionality reduction by transforming a dataset into a new coordinate system. The transformation emphasizes the directions (principal components) that maximize the variance in the data, helping to reduce the number of features while preserving essential information. ==Key Concepts== *'''Principal Components:''' New orthogonal axes computed as linear combinations of the original features. The first pr... Tag: Visual edit
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