ColorPCA: Scalable Colored Dimensionality Reduction for Unlabeled High-Dimensional Data

ColorPCA: Scalable Colored Dimensionality Reduction for Unlabeled High-Dimensional Data

Mapping labeled high-dimensional data to colors based on class labels in low-dimensional projections is effective for enhancing pattern recognition and reducing misinterpretation of clusters. However, automatic coloring of unlabeled high-dimensional data remains challenging for revealing unknown pat...

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Bibliographic Details
Main Authors: Wenqiang Cui, Shehzad Afzal, Rafael M. Martins, Sohaib Ghani, Ibrahim Hoteit
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
High-dimensional data
dimensionality reduction
color mapping
color contrast enhancement
unlabeled data
data visualization
Online Access:https://ieeexplore.ieee.org/document/11021415/
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https://ieeexplore.ieee.org/document/11021415/

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