Dimensionality Reduction: Revision history

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    1 December 2024

    • curprev 16:0916:09, 1 December 2024‎ Dendrogram talk contribs‎ 3,754 bytes +3,754‎ 새 문서: '''Dimensionality Reduction''' is a technique used in machine learning and data analysis to reduce the number of features (dimensions) in a dataset while preserving as much relevant information as possible. It simplifies data visualization, reduces computational costs, and helps mitigate the curse of dimensionality. ==Importance of Dimensionality Reduction== Dimensionality reduction is crucial for the following reasons: *'''Improves Model Performance:''' Reducing irrelevant or r... Tag: Visual edit
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