Pages that link to "Item:Q855920"
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The following pages link to Minimum distance classification rules for high dimensional data (Q855920):
Displaying 10 items.
- Asymptotic properties of the misclassification rates for Euclidean distance discriminant rule in high-dimensional data (Q495367) (← links)
- Effective PCA for high-dimension, low-sample-size data with noise reduction via geometric representations (Q764487) (← links)
- On the orthogonal distance to class subspaces for high-dimensional data classification (Q778457) (← links)
- Minimal sample size in the group classification problem (Q818986) (← links)
- Robust centroid based classification with minimum error rates for high dimension, low sample size data (Q1021991) (← links)
- A \(U\)-classifier for high-dimensional data under non-normality (Q1661350) (← links)
- Two-group classification with high-dimensional correlated data: a factor model approach (Q2275650) (← links)
- Change-Point Detection of the Mean Vector with Fewer Observations than the Dimension Using Instantaneous Normal Random Projections (Q2833372) (← links)
- The Asymptotic Approximation of EPMC for Linear Discriminant Rules Using a Moore-Penrose Inverse Matrix in High Dimension (Q2862312) (← links)
- Estimation in High-Dimensional Analysis and Multivariate Linear Models (Q3006260) (← links)
