Pages that link to "Item:Q1763097"

The following pages link to Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations (Q1763097):

Displaying 50 items.

• High dimensional classifiers in the imbalanced case (Q1659246) (← links)
• A \(U\)-classifier for high-dimensional data under non-normality (Q1661350) (← links)
• Network linear discriminant analysis (Q1662034) (← links)
• Continuum directions for supervised dimension reduction (Q1662921) (← links)
• Sparse HDLSS discrimination with constrained data piling (Q1663205) (← links)
• Distribution-free high-dimensional two-sample tests based on discriminating hyperplanes (Q1694021) (← links)
• Simultaneous variable selection and class fusion with penalized distance criterion based classifiers (Q1727900) (← links)
• A multiple testing approach to the regularisation of large sample correlation matrices (Q1739875) (← links)
• High-dimensional asymptotics of prediction: ridge regression and classification (Q1747738) (← links)
• Persistene in high-dimensional linear predictor-selection and the virtue of overparametrization (Q1763096) (← links)
• On the dimension effect of regularized linear discriminant analysis (Q1786573) (← links)
• Optimal feature selection for sparse linear discriminant analysis and its applications in gene expression data (Q1800123) (← links)
• Variable selection in linear mixed effects models (Q1940766) (← links)
• Comparison of binary discrimination methods for high dimension low sample size data (Q1941430) (← links)
• Sparse permutation invariant covariance estimation (Q1951760) (← links)
• High dimensional sparse covariance estimation via directed acyclic graphs (Q1952020) (← links)
• A method for selecting the relevant dimensions for high-dimensional classification in singular vector spaces (Q1999449) (← links)
• Distance-based classifier by data transformation for high-dimension, strongly spiked eigenvalue models (Q2000734) (← links)
• Variational nonparametric discriminant analysis (Q2008105) (← links)
• Classification with many classes: challenges and pluses (Q2008227) (← links)
• High-dimensional linear models: a random matrix perspective (Q2051014) (← links)
• Geometric classifiers for high-dimensional noisy data (Q2062792) (← links)
• Large-sample properties of unsupervised estimation of the linear discriminant using projection pursuit (Q2074341) (← links)
• Varying coefficient linear discriminant analysis for dynamic data (Q2084480) (← links)
• New hard-thresholding rules based on data splitting in high-dimensional imbalanced classification (Q2136627) (← links)
• Optimal functional supervised classification with separation condition (Q2174981) (← links)
• Variational discriminant analysis with variable selection (Q2195837) (← links)
• A procedure of linear discrimination analysis with detected sparsity structure for high-dimensional multi-class classification (Q2196123) (← links)
• High dimensional classification for spatially dependent data with application to neuroimaging (Q2209817) (← links)
• Beyond HC: more sensitive tests for rare/weak alternatives (Q2215733) (← links)
• Regularized principal components of heritability (Q2259728) (← links)
• Two-group classification with high-dimensional correlated data: a factor model approach (Q2275650) (← links)
• Ensemble quantile classifier (Q2291292) (← links)
• Conditional probability estimation based classification with class label missing at random (Q2293539) (← links)
• Dynamic linear discriminant analysis in high dimensional space (Q2295032) (← links)
• Pairwise local Fisher and naive Bayes: improving two standard discriminants (Q2305993) (← links)
• Random projections as regularizers: learning a linear discriminant from fewer observations than dimensions (Q2353006) (← links)
• Data mining in electronic commerce (Q2381785) (← links)
• Persistence of plug-in rule in classification of high dimensional multivariate binary data (Q2382893) (← links)
• Graph-based sparse linear discriminant analysis for high-dimensional classification (Q2418517) (← links)
• Penalized model-based clustering (Q2426832) (← links)
• A guided random walk through some high dimensional problems (Q2431011) (← links)
• Optimal classification in sparse Gaussian graphic model (Q2438761) (← links)
• Covariance and precision matrix estimation for high-dimensional time series (Q2443210) (← links)
• Random matrix theory in statistics: a review (Q2453609) (← links)
• Bayesian variable selection for high dimensional generalized linear models: convergence rates of the fitted densities (Q2456008) (← links)
• The delta method for analytic functions of random operators with application to functional data (Q2469671) (← links)
• Regularized estimation of large covariance matrices (Q2477058) (← links)
• Sparse estimation of large covariance matrices via a nested Lasso penalty (Q2482977) (← links)
• High dimensional covariance matrix estimation using multi-factor models from incomplete information (Q2515313) (← links)