Feature Import Vector Machine: A General Classifier with Flexible Feature Selection [0.03%]
具有灵活特征选择的通用分类器-特征重要向量机
Samiran Ghosh,Yazhen Wang
Samiran Ghosh
The support vector machine (SVM) and other reproducing kernel Hilbert space (RKHS) based classifier systems are drawing much attention recently due to its robustness and generalization capability. General theme here is to construct classifi...
Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods [0.03%]
利用递归剥离法进行生存分析中的交叉验证和剥离策略以寻找突起部分的方法研究
Jean-Eudes Dazard,Michael Choe,Michael LeBlanc et al.
Jean-Eudes Dazard et al.
We introduce a framework to build a survival/risk bump hunting model with a censored time-to-event response. Our Survival Bump Hunting (SBH) method is based on a recursive peeling procedure that uses a specific survival peeling criterion de...
Prediction using hierarchical data: Applications for automated detection of cervical cancer [0.03%]
基于分层数据的预测：自动检测宫颈癌的应用
Jose-Miguel Yamal,Martial Guillaud,E Neely Atkinson et al.
Jose-Miguel Yamal et al.
Although the Papanicolaou smear has been successful in decreasing cervical cancer incidence in the developed world, there exist many challenges for implementation in the developing world. Quantitative cytology, a semi-automated method that ...
A Novel Support Vector Classifier for Longitudinal High-dimensional Data and Its Application to Neuroimaging Data [0.03%]
一种用于纵向高维数据的新型支持向量分类器及其在神经影像数据中的应用
Shuo Chen,F DuBois Bowman
Shuo Chen
Recent technological advances have made it possible for many studies to collect high dimensional data (HDD) longitudinally, for example images collected during different scanning sessions. Such studies may yield temporal changes of selected...
Regularized Partial Least Squares with an Application to NMR Spectroscopy [0.03%]
正则化部分最小二乘法及其在核磁共振光谱学中的应用
Genevera I Allen,Christine Peterson,Marina Vannucci et al.
Genevera I Allen et al.
High-dimensional data common in genomics, proteomics, and chemometrics often contains complicated correlation structures. Recently, partial least squares (PLS) and Sparse PLS methods have gained attention in these areas as dimension reducti...
Stacey J Winham,Robert R Freimuth,Joanna M Biernacka
Stacey J Winham
Identifying genetic variants associated with complex disease in high-dimensional data is a challenging problem, and complicated etiologies such as gene-gene interactions are often ignored in analyses. The data-mining method Random Forests (...
Multiple Response Regression for Gaussian Mixture Models with Known Labels [0.03%]
具有已知标签的高斯混合模型的多响应回归
Wonyul Lee,Ying Du,Wei Sun et al.
Wonyul Lee et al.
Multiple response regression is a useful regression technique to model multiple response variables using the same set of predictor variables. Most existing methods for multiple response regression are designed for modeling homogeneous data....
Yiping Yuan,Xiaotong Shen,Wei Pan
Yiping Yuan
Estimation of multiple directed graphs becomes challenging in the presence of inhomogeneous data, where directed acyclic graphs (DAGs) are used to represent causal relations among random variables. To infer causal relations among variables,...
Penalized Regression and Risk Prediction in Genome-Wide Association Studies [0.03%]
惩罚回归及全基因组关联研究中的风险预测模型
Erin Austin,Wei Pan,Xiaotong Shen
Erin Austin
An important task in personalized medicine is to predict disease risk based on a person's genome, e.g. on a large number of single-nucleotide polymorphisms (SNPs). Genome-wide association studies (GWAS) make SNP and phenotype data available...
Anna J Blackstock,Amita K Manatunga,Youngja Park et al.
Anna J Blackstock et al.
Nuclear magnetic resonance (NMR) spectroscopy, traditionally used in analytical chemistry, has recently been introduced to studies of metabolite composition of biological fluids and tissues. Metabolite levels change over time, and providing...