Pages that link to "Item:Q5959968"

The following pages link to Gene selection for cancer classification using support vector machines (Q5959968):

Displaying 50 items.

• Correlation and variable importance in random forests (Q58729) (← links)
• A user-guided Bayesian framework for ensemble feature selection in life science applications (UBayFS) (Q71870) (← links)
• Feature selection with SVD entropy: some modification and extension (Q278695) (← links)
• Feature subset selection for logistic regression via mixed integer optimization (Q301699) (← links)
• Finding causative genes from high-dimensional data: an appraisal of statistical and machine learning approaches (Q309421) (← links)
• Fuzzy rough based regularization in generalized multiple kernel learning (Q316269) (← links)
• DC approximation approaches for sparse optimization (Q319281) (← links)
• Feature selection for support vector machines using generalized Benders decomposition (Q319318) (← links)
• Sparse Bayesian multinomial probit regression model with correlation prior for high-dimensional data classification (Q334051) (← links)
• Supervised classification and mathematical optimization (Q339559) (← links)
• A multiobjective based approach for mathematical programs with linear flexible constraints (Q345535) (← links)
• Clustering and feature selection using sparse principal component analysis (Q374668) (← links)
• Multiple suboptimal solutions for prediction rules in gene expression data (Q382664) (← links)
• Parameterized attribute reduction with Gaussian kernel based fuzzy rough sets (Q424767) (← links)
• Sparse PCA by iterative elimination algorithm (Q429783) (← links)
• Learning sparse gradients for variable selection and dimension reduction (Q439003) (← links)
• A novel weighted support vector machine based on particle swarm optimization for gene selection and tumor classification (Q454637) (← links)
• Recursive feature selection with significant variables of support vectors (Q454723) (← links)
• Sparse regression and support recovery with \(\mathbb{L}_2\)-boosting algorithms (Q466526) (← links)
• Lagrangian support vector regression via unconstrained convex minimization (Q470224) (← links)
• Rank discriminants for predicting phenotypes from RNA expression (Q484006) (← links)
• Feature selection for support vector machines via mixed integer linear programming (Q506302) (← links)
• Cancer feature selection and classification using a binary quantum-behaved particle swarm optimization and support vector machine (Q519834) (← links)
• A generalized eigenvalues classifier with embedded feature selection (Q526414) (← links)
• Learning gradients on manifolds (Q605040) (← links)
• On the distance concentration awareness of certain data reduction techniques (Q614077) (← links)
• BASSUM: a Bayesian semi-supervised method for classification feature selection (Q621082) (← links)
• Network-based sparse Bayesian classification (Q621090) (← links)
• A method for visual identification of small sample subgroups and potential biomarkers (Q652375) (← links)
• Adaptive sequential design for regression on multi-resolution bases (Q693303) (← links)
• Learning the coordinate gradients (Q695644) (← links)
• Selection bias in working with the top genes in supervised classification of tissue samples (Q713676) (← links)
• Designing a hybrid intelligent mining system for credit risk evaluation (Q732812) (← links)
• A computer-aided diagnosis system for dynamic contrast-enhanced MR images based on level set segmentation and ReliefF feature selection (Q738278) (← links)
• A centroid-based gene selection method for microarray data classification (Q738623) (← links)
• Machine learning approaches for discrimination of extracellular matrix proteins using hybrid feature space (Q738768) (← links)
• Classification of signaling proteins based on molecular star graph descriptors using machine learning models (Q739721) (← links)
• Data mining methods for gene selection on the basis of gene expression arrays (Q747425) (← links)
• Double regularization methods for robust feature selection and SVM classification via DC programming (Q781867) (← links)
• High-dimensional model recovery from random sketched data by exploring intrinsic sparsity (Q782446) (← links)
• Predictor output sensitivity and feature similarity-based feature selection (Q834484) (← links)
• Feature selection via Boolean independent component analysis (Q845317) (← links)
• Terminated Ramp--Support Vector machines: A nonparametric data dependent kernel (Q858897) (← links)
• Stochastic local search for the FEATURE SET problem, with applications to microarray data (Q865564) (← links)
• An efficient \(k\) nearest neighbor search for multivariate time series (Q868028) (← links)
• Large margin subspace learning for feature selection (Q888576) (← links)
• Using causal discovery for feature selection in multivariate numerical time series (Q890305) (← links)
• Joint Laplacian feature weights learning (Q898384) (← links)
• From genome-scale data to models of infectious disease: a Bayesian network-based strategy to drive model development (Q899417) (← links)
• A Bayesian hybrid huberized support vector machine and its applications in high-dimensional medical data (Q901503) (← links)