Pages that link to "Item:Q4468366"

The following pages link to Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data (Q4468366):

Displaying 50 items.

• Improved methods for the imputation of missing data by nearest neighbor methods (Q1663207) (← links)
• Comparisons of classification methods for viral genomes and protein families using alignment-free vectorization (Q1672834) (← links)
• Integrated use of statistical-based approaches and computational intelligence techniques for tumors classification using microarray (Q1723248) (← links)
• Regression adjustment for treatment effect with multicollinearity in high dimensions (Q1727920) (← links)
• Consistency of large dimensional sample covariance matrix under weak dependence (Q1731211) (← links)
• Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations (Q1763097) (← links)
• Multi-class clustering and prediction in the analysis of microarray data (Q1776767) (← links)
• Bandwidth choice for nonparametric classification (Q1781162) (← links)
• RFCRYS: sequence-based protein crystallization propensity prediction by means of random forest (Q1784813) (← links)
• On the dimension effect of regularized linear discriminant analysis (Q1786573) (← links)
• A new geometric biclustering algorithm based on the Hough transform for analysis of large-scale microarray data (Q1788649) (← links)
• A truncation algorithm for minimizing the Frobenius-Schatten norm to find a sparse matrix (Q1792415) (← links)
• Optimal feature selection for sparse linear discriminant analysis and its applications in gene expression data (Q1800123) (← links)
• Clustering and classification based on the L\(_{1}\) data depth (Q1876982) (← links)
• Finding predictive gene groups from microarray data (Q1876985) (← links)
• Separable linear discriminant analysis (Q1927211) (← links)
• Predicting partial customer churn using Markov for discrimination for modeling first purchase sequences (Q1928210) (← links)
• Variable selection in linear mixed effects models (Q1940766) (← links)
• Regularized \(k\)-means clustering of high-dimensional data and its asymptotic consistency (Q1950809) (← links)
• PPtree: projection pursuit classification tree (Q1951161) (← links)
• Penalized model-based clustering with unconstrained covariance matrices (Q1952033) (← 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)
• Graphical tools for model-based mixture discriminant analysis (Q2009043) (← links)
• A distribution-based Lasso for a general single-index model (Q2018911) (← links)
• Sphericity and identity test for high-dimensional covariance matrix using random matrix theory (Q2025160) (← links)
• Kick-one-out-based variable selection method for Euclidean distance-based classifier in high-dimensional settings (Q2034468) (← links)
• The horseshoe-like regularization for feature subset selection (Q2040669) (← links)
• Affine-transformation invariant clustering models (Q2040902) (← links)
• Geometric classifiers for high-dimensional noisy data (Q2062792) (← links)
• A sparse negative binomial classifier with covariate adjustment for RNA-seq data (Q2154214) (← links)
• Weighted Lasso estimates for sparse logistic regression: non-asymptotic properties with measurement errors (Q2154741) (← links)
• Independence index sufficient variable screening for categorical responses (Q2157537) (← links)
• Tumor classification using phylogenetic methods on expression data (Q2187663) (← links)
• Detecting differentially expressed genes by relative entropy (Q2193153) (← links)
• Fast approximate inference for variable selection in Dirichlet process mixtures, with an application to pan-cancer proteomics (Q2195280) (← links)
• Variational discriminant analysis with variable selection (Q2195837) (← links)
• Variable selection for binary classification in large dimensions: comparisons and application to microarray data (Q2197385) (← links)
• Estimations for some functions of covariance matrix in high dimension under non-normality and its applications (Q2252884) (← links)
• Biomarker discovery: classification using pooled samples (Q2255767) (← links)
• Partial least squares classification for high dimensional data using the PCOUT algorithm (Q2255855) (← links)
• Applications of Bayesian gene selection and classification with mixtures of generalized singular \(g\)-priors (Q2262183) (← links)
• Comparison of different EHG feature selection methods for the detection of preterm labor (Q2262213) (← links)
• A probabilistic relaxation labeling framework for reducing the noise effect in geometric biclustering of gene expression data (Q2270726) (← links)
• A nonparametric test for block-diagonal covariance structure in high dimension and small samples (Q2274963) (← links)
• Two-group classification with high-dimensional correlated data: a factor model approach (Q2275650) (← links)
• Blockwise projection matrix versus blockwise data on undersampled problems: analysis, comparison and applications (Q2276016) (← links)
• Classification tree algorithm for grouped variables (Q2282589) (← links)
• Ensemble quantile classifier (Q2291292) (← links)
• Tuning parameter calibration for \(\ell_1\)-regularized logistic regression (Q2317308) (← links)