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.

• Proximal gradient method for huberized support vector machine (Q2337512) (← links)
• Random projections as regularizers: learning a linear discriminant from fewer observations than dimensions (Q2353006) (← links)
• Using visual statistical inference to better understand random class separations in high dimension, low sample size data (Q2354730) (← links)
• Bayesian variable selection in multinomial probit model for classifying high-dimensional data (Q2354735) (← links)
• Bayesian variable selection with sparse and correlation priors for high-dimensional data analysis (Q2358912) (← links)
• Sparse sufficient dimension reduction using optimal scoring (Q2359474) (← links)
• Comparability of gene expression in human blood, immune and carcinoma cells (Q2378753) (← links)
• Asymptotic inference for high-dimensional data (Q2380091) (← links)
• Optimal properties of centroid-based classifiers for very high-dimensional data (Q2380097) (← links)
• Cancer classification using ensemble of neural networks with multiple significant gene subsets (Q2383957) (← links)
• A simultaneous testing of the mean vector and the covariance matrix among two populations for high-dimensional data (Q2414881) (← links)
• Estimation of multivariate 3rd moment for high-dimensional data and its application for testing multivariate normality (Q2418080) (← links)
• Variable selection for multicategory SVM via adaptive sup-norm regularization (Q2426830) (← links)
• Penalized model-based clustering (Q2426832) (← links)
• Monotone false discovery rate (Q2452877) (← links)
• Marginal asymptotics for the ``large \(p\), small \(n\)'' paradigm: with applications to microarray data (Q2456007) (← links)
• Molecular gene expression signature patterns for gastric cancer diagnosis (Q2459121) (← links)
• Development and validation of biomarker classifiers for treatment selection (Q2475718) (← links)
• Several biplot methods applied to gene expression data (Q2475736) (← links)
• A test for the mean vector with fewer observations than the dimension (Q2476142) (← links)
• Reducing multiclass cancer classification to binary by output coding and SVM (Q2490524) (← links)
• Classifying G-protein coupled receptors with bagging classification tree (Q2490541) (← links)
• Multi-class tumor classification by discriminant partial least squares using microarray gene expression data and assessment of classification models (Q2490602) (← links)
• Boosting for high-dimensional linear models (Q2497175) (← links)
• Stability of feature selection in classification issues for high-dimensional correlated data (Q2628882) (← links)
• Non-parametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices (Q2637612) (← links)
• Markov blanket-embedded genetic algorithm for gene selection (Q2643912) (← links)
• A weight function method for selection of proteins to predict an outcome using protein expression data (Q2656115) (← links)
• Comparing the linear and quadratic discriminant analysis of diabetes disease classification based on data multicollinearity (Q2693273) (← links)
• Effective dimensionality reduction using kernel locality preserving partial least squares discriminant analysis (Q2699576) (← links)
• Estimating prediction error in microarray classification: modifications of the 0.632+ bootstrap when \(n<p\) (Q2852557) (← links)
• The Asymptotic Approximation of EPMC for Linear Discriminant Rules Using a Moore-Penrose Inverse Matrix in High Dimension (Q2862312) (← links)
• Tilting methods for assessing the influence of components in a classifier (Q2920282) (← links)
• Penalized Independence Rule for Testing High-Dimensional Hypotheses (Q3017854) (← links)
• CLASSIFICATION OF HIGH-DIMENSIONAL MICROARRAY DATA WITH A TWO-STEP PROCEDURE VIA A WILCOXON CRITERION AND MULTILAYER PERCEPTRON (Q3019526) (← links)
• Evolutionary Tolerance-Based Gene Selection in Gene Expression Data (Q3019856) (← links)
• Bias-Corrected Diagonal Discriminant Rules for High-Dimensional Classification (Q3076039) (← links)
• Characterizing the Relationship Between HIV-1 Genotype and Phenotype: Prediction-Based Classification (Q3078915) (← links)
• Combining Several Screening Tests: Optimality of the Risk Score (Q3079005) (← links)
• Robust penalized logistic regression with truncated loss functions (Q3087592) (← links)
• Two-Stage Procedures for High-Dimensional Data (Q3106536) (← links)
• A DC Programming Approach for Sparse Linear Discriminant Analysis (Q3192955) (← links)
• Geometric Classifier for Multiclass, High-Dimensional Data (Q3194547) (← links)
• A method for constructing a confidence bound for the actual error rate of a prediction rule in high dimensions (Q3304962) (← links)
• Variable selection and dependency networks for genomewide data (Q3304982) (← links)
• Robust depth-based tools for the analysis of gene expression data (Q3305017) (← links)
• Comparison of Support Vector Machines to Other Classifiers Using Gene Expression Data (Q3378036) (← links)
• Bayesian variable selection in clustering high-dimensional data via a mixture of finite mixtures (Q3389640) (← links)
• Multiclass Probability Estimation With Support Vector Machines (Q3391267) (← links)
• Diagonal Discriminant Analysis With Feature Selection for High-Dimensional Data (Q3391457) (← links)