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.

• A Bayesian hybrid huberized support vector machine and its applications in high-dimensional medical data (Q901503) (← links)
• Gene selection and prediction for cancer classification using support vector machines with a reject option (Q901576) (← links)
• Improved Stein-type shrinkage estimators for the high-dimensional multivariate normal covariance matrix (Q901577) (← links)
• The EM algorithm and the rise of computational biology (Q906519) (← links)
• Simultaneous classification and relevant feature identification in high-dimensional spaces: Application to molecular profiling data (Q947408) (← links)
• Estimation of the precision matrix of a singular Wishart distribution and its application in high-dimensional data (Q953851) (← links)
• On partial least squares dimension reduction for microarray-based classification: a simulation study (Q956938) (← links)
• Stable classification with applications to microarray data (Q957037) (← links)
• An extensive comparison of recent classification tools applied to microarray data (Q957169) (← links)
• Bundling classifiers by bagging trees (Q957281) (← links)
• Identification of interaction patterns and classification with applications to microarray data (Q959203) (← links)
• Efficient multi-class cancer diagnosis algorithm, using a global similarity pattern (Q961182) (← links)
• Simultaneous cancer classification and gene selection with Bayesian nearest neighbor method: an integrated approach (Q961289) (← links)
• Survival prediction using gene expression data: a review and comparison (Q961312) (← links)
• Modified linear discriminant analysis approaches for classification of high-dimensional microarray data (Q961326) (← links)
• A robust unified approach to analyzing methylation and gene expression data (Q961331) (← links)
• Selecting marker genes for cancer classification using supervised weighted kernel clustering and the support vector machine (Q961343) (← links)
• Simple Bayesian binary framework for discovering significant genes and classifying cancer diagnosis (Q961344) (← links)
• A flexible approximate likelihood ratio test for detecting differential expression in microarray data (Q961838) (← links)
• Bayesian binary kernel probit model for microarray based cancer classification and gene selection (Q961916) (← links)
• Pattern recognition via projection-based \(k\)NN rules (Q962393) (← links)
• A new and fast implementation for null space based linear discriminant analysis (Q962681) (← links)
• Visualization of ``high \(p\) small \(n\)'' data (Q964635) (← links)
• Sparse Bayesian hierarchical modeling of high-dimensional clustering problems (Q972898) (← links)
• Asymptotic properties of the EPMC for modified linear discriminant analysis when sample size and dimension are both large (Q974518) (← links)
• High-dimensional classification using features annealed independence rules (Q1000303) (← links)
• Sparse optimal scoring for multiclass cancer diagnosis and biomarker detection using microarray data (Q1004954) (← links)
• Optimal classification for time-course gene expression data using functional data analysis (Q1004958) (← links)
• Multiclass sparse logistic regression for classification of multiple cancer types using gene expression data (Q1010516) (← links)
• Local likelihood regression in generalized linear single-index models with applications to microarray data (Q1010557) (← links)
• Classification by ensembles from random partitions of high-dimensional data (Q1020719) (← links)
• Class prediction and gene selection for DNA microarrays using regularized sliced inverse regression (Q1020831) (← links)
• High-dimensional pseudo-logistic regression and classification with applications to gene expression data (Q1020833) (← links)
• Discrimination of locally stationary time series using wavelets (Q1020891) (← links)
• Outlier identification in high dimensions (Q1023500) (← links)
• Estimation of the conditional risk in classification: the swapping method (Q1023660) (← links)
• Cancer classification using gene expression data. (Q1400608) (← links)
• Statistical challenges in functional genomics. (With comments and a rejoinder). (Q1431220) (← links)
• Variable selection and pattern recognition with gene expression data generated by the microarray technology (Q1602590) (← links)
• Dimension reduction strategies for analyzing global gene expression data with a response (Q1602593) (← links)
• Sequential double cross-validation for assessment of added predictive ability in high-dimensional omic applications (Q1621008) (← links)
• On selecting interacting features from high-dimensional data (Q1621350) (← links)
• Stein's method in high dimensional classification and applications (Q1623745) (← links)
• Nonparametric Stein-type shrinkage covariance matrix estimators in high-dimensional settings (Q1623798) (← links)
• A moment-distance hybrid method for estimating a mixture of two symmetric densities (Q1641931) (← links)
• High dimensional covariance matrix estimation by penalizing the matrix-logarithm transformed likelihood (Q1658345) (← links)
• The use of random-effect models for high-dimensional variable selection problems (Q1659014) (← links)
• Robust groupwise least angle regression (Q1660232) (← links)
• A \(U\)-classifier for high-dimensional data under non-normality (Q1661350) (← links)
• Sparse HDLSS discrimination with constrained data piling (Q1663205) (← links)