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.

• Design Considerations for Efficient and Effective Microarray Studies (Q3433210) (← links)
• Penalized Discriminant Methods for the Classification of Tumors from Gene Expression Data (Q3433236) (← links)
• Parametric and Nonparametric FDR Estimation Revisited (Q3436516) (← links)
• A Multivariate Two-Sample Mean Test for Small Sample Size and Missing Data (Q3436536) (← links)
• Comparison of Statistical Classification Methods Based on a Prostate Cancer Study (Q3442948) (← links)
• Modeling Microarray Data Using a Threshold Mixture Model (Q3442966) (← links)
• Systematic benchmarking of microarray data feature extraction and classification (Q3506258) (← links)
• Variable Selection in Penalized Model‐Based Clustering Via Regularization on Grouped Parameters (Q3530115) (← links)
• Statistical analysis of C‐DNA microarray data for sample clustering and gene identification (Q3530682) (← links)
• A review of modern multiple hypothesis testing, with particular attention to the false discovery proportion (Q3597112) (← links)
• Rank-Based Classification Using Robust Discriminant Functions (Q3616263) (← links)
• A Robust Maximal <i>F</i>-Ratio Statistic to Detect Clusters Structure (Q3622081) (← links)
• A nonparametric allocation scheme for classification based on transvariation probabilities (Q3638529) (← links)
• Meta‐learning approach to gene expression data classification (Q3639489) (← links)
• Gene Expression Analysis by Fuzzy and Hybrid Fuzzy Classification (Q3652858) (← links)
• Selection bias in gene extraction on the basis of microarray gene-expression data (Q4547711) (← links)
• Statistical inference for high-dimension, low-sample-size data (Q4568290) (← links)
• Spectral Pattern Comparison Methods for Cancer Classification Based on Microarray Gene Expression Data (Q4590511) (← links)
• Aggregating classifiers with ordinal response structure (Q4675843) (← links)
• GENE SELECTION USING LOGISTIC REGRESSIONS BASED ON AIC, BIC AND MDL CRITERIA (Q4679772) (← links)
• Identifying Soccer Players on Facebook Through Predictive Analytics (Q4692043) (← links)
• A comparison of regularization methods applied to the linear discriminant function with high-dimensional microarray data (Q4922655) (← links)
• An Improved Method on Wilcoxon Rank Sum Test for Gene Selection from Microarray Experiments (Q4929226) (← links)
• Fully Bayesian logistic regression with hyper-LASSO priors for high-dimensional feature selection (Q4960726) (← links)
• Multicategory composite least squares classifiers (Q4969725) (← links)
• (Q5011468) (← links)
• Classification using semiparametric mixtures (Q5034169) (← links)
• Intelligent predicting reaction performance in multi-dimensional chemical space using quantile regression forest (Q5051955) (← links)
• A resample-replace lasso procedure for combining high-dimensional markers with limit of detection (Q5056946) (← links)
• A classifier under the strongly spiked eigenvalue model in high-dimension, low-sample-size context (Q5077372) (← links)
• Robust tests of the equality of two high-dimensional covariance matrices (Q5081046) (← links)
• Robust support vector machine for high-dimensional imbalanced data (Q5082626) (← links)
• High-dimensional Canonical Forest (Q5106824) (← links)
• Fast Bayesian variable screenings for binary response regressions with small sample size (Q5106969) (← links)
• An improved modified cholesky decomposition approach for precision matrix estimation (Q5107717) (← links)
• A permutation test approach to the choice of size<i>k</i>for the nearest neighbors classifier (Q5124918) (← links)
• Performance Comparison of Machine Learning Platforms (Q5138254) (← links)
• A link-free sparse group variable selection method for single-index model (Q5138715) (← links)
• A New Test on High-Dimensional Mean Vector Without Any Assumption on Population Covariance Matrix (Q5177621) (← links)
• Hierarchical mixture models for biclustering in microarray data (Q5193318) (← links)
• (Q5211853) (← links)
• Tests for high-dimensional covariance matrices using the theory of<i>U</i>-statistics (Q5220895) (← links)
• A simple model‐based approach to variable selection in classification and clustering (Q5256376) (← links)
• Modified linear discriminant analysis using block covariance matrix in high-dimensional data (Q5267876) (← links)
• High-Dimensional Data Classification (Q5270620) (← links)
• Forward selection method with regression analysis for optimal gene selection in cancer classification (Q5294693) (← links)
• Properties of Bagged Nearest Neighbour Classifiers (Q5313456) (← links)
• Bayesian Classification of Tumours by Using Gene Expression Data (Q5313586) (← links)
• Classification of Higher-order Data with Separable Covariance and Structured Multiplicative or Additive Mean Models (Q5419342) (← links)
• Selection of Binary Variables and Classification by Boosting (Q5436402) (← links)