Principal Component Analysis Visualization
Principal Component Analysis Visualization is a dimensionality reduction visualization technique that transforms high-dimensional data into a lower-dimensional space by projecting it onto orthogonal axes of maximum variance, enabling interpretable visual patterns through principal component scores.
59
Publications
11.6K
Citations
175
Authors
87
Institutions
Publications per year
2017–2026
18
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175
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87

University of New Hampshire
Durham, United States
2 h-index
4 publications
96 citations
Universidad Nacional de Entre Ríos
Concepción del Uruguay, Argentina
2 h-index
4 publications
242 citations

Lund University
Lund, Sweden
2 h-index
3 publications
436 citations
Rotterdam University of Applied Sciences
Rotterdam, Netherlands
1 h-index
3 publications
69 citations
University of California, San Francisco
San Francisco, United States
1 h-index
5 publications
155 citations

San Francisco General Hospital
San Francisco, United States
1 h-index
5 publications
155 citations
Neurological Surgery
Rockville Centre, United States
1 h-index
5 publications
155 citations

University of Helsinki
Helsinki, Finland
1 h-index
5 publications
115 citations
1–8 of 87
JCGS · 4 publications · 444 citations
4
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3 publications · 153 citations
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2 publications · 310 citations
2
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2 publications · 3.2K citations
2
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2 publications · 87 citations
2
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1–5