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insikt - Dimensionality Reduction Techniques
Density-based Isometric Mapping for Precision Medicine
The author introduces a novel method, PR-Isomap, to project high-dimensional data into a lower-dimensional space while preserving both local and global distances. By modifying the Isomap algorithm with a Parzen-Rosenblatt constraint, the approach aims to enhance uniformity and maintain geodesic distance approximation.
DiffRed: Dimensionality Reduction Guided by Stable Rank
DiffRed introduces a novel approach to dimensionality reduction guided by stable rank, achieving tighter bounds on M1 and Stress metrics. The algorithm leverages stable rank to optimize the target dimensions for reduced distortion.
DiffRed: Dimensionality Reduction guided by stable rank
DiffRed introduces a novel approach to dimensionality reduction guided by stable rank, achieving lower distortion metrics compared to traditional techniques.
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