The maximal data piling direction for discrimination
From MaRDI portal
Publication:5305488
DOI10.1093/biomet/asp084zbMath1182.62134OpenAlexW2027688434MaRDI QIDQ5305488
Jeongyoun Ahn, James Stephen Marron
Publication date: 22 March 2010
Published in: Biometrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1093/biomet/asp084
text classificationsupport vector machinehigh dimensionlow sample sizeFisher's linear discriminationmaximal data piling
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics (62P99)
Related Items (26)
Distance-based outlier detection for high dimension, low sample size data ⋮ New hard-thresholding rules based on data splitting in high-dimensional imbalanced classification ⋮ Fully Three-Dimensional Radial Visualization ⋮ Trace Ratio Optimization for High-Dimensional Multi-Class Discrimination ⋮ Overview of object oriented data analysis ⋮ General sparse multi-class linear discriminant analysis ⋮ A generalized likelihood ratio test for normal mean when \(p\) is greater than \(n\) ⋮ Continuum directions for supervised dimension reduction ⋮ Sparse HDLSS discrimination with constrained data piling ⋮ Robust support vector machine for high-dimensional imbalanced data ⋮ Burning Sage: Reversing the Curse of Dimensionality in the Visualization of High-Dimensional Data ⋮ Support vector machine and its bias correction in high-dimension, low-sample-size settings ⋮ On the border of extreme and mild spiked models in the HDLSS framework ⋮ Unnamed Item ⋮ A robust support vector machine for labeling errors ⋮ A survey of high dimension low sample size asymptotics ⋮ Binary discrimination methods for high-dimensional data with a geometric representation ⋮ Distance-based classifier by data transformation for high-dimension, strongly spiked eigenvalue models ⋮ Treelets -- an adaptive multi-scale basis for sparse unordered data ⋮ Subspace rotations for high-dimensional outlier detection ⋮ Bias-corrected support vector machine with Gaussian kernel in high-dimension, low-sample-size settings ⋮ Interpretation of Black-Box Predictive Models ⋮ Geometric insights into support vector machine behavior using the KKT conditions ⋮ Double data piling leads to perfect classification ⋮ More about asymptotic properties of some binary classification methods for high dimensional data ⋮ Unnamed Item
This page was built for publication: The maximal data piling direction for discrimination