搜索结果: 1-7 共查到“数学 Feature”相关记录7条 . 查询时间(0.046 秒)
Higher Criticism Thresholding: Optimal Feature Selection when Useful Features are Rare and Weak
Criticism Thresholding Feature Selection
2015/8/21
Linear classi cation analysis is a fundamental tool for science
and technology. In important application elds today { genomics and proteomics are examples { one automatically obtains very high-dimen...
Feature Extraction for Nonparametric Discriminant Analysis
ClassiŽ cation Density estimation Dimension reduction LDA Projection pursuit Reduced-rankmodel SAVE
2015/8/21
In high-dimensional classification problems, one is often interested in ?? finding a few important discriminant directions in order to reduce the dimensionality.Fisher’s linear discriminant analysis(L...
“PRECONDITIONING” FOR FEATURE SELECTION AND REGRESSION IN HIGH-DIMENSIONAL PROBLEMS
Model selection prediction error lasso
2015/8/21
We consider regression problems where the number of predictors greatly exceeds the number of observations. We propose a method for variable selection that first estimates the regression function, yiel...
Pattern Recognition with Slow Feature Analysis
Characteristic analysis nonlinear function the input data the function of learning
2015/7/31
Slow feature analysis (SFA) is a new unsupervised algorithm to learn nonlinear functions that extract slowly varying signals out of the input data. In this paper we describe its application to pattern...
Feature-scale Simulations of Particulate Slurry Flows in Chemical Mechanical Polishing by Smoothed Particle Hydrodynamics
Chemical mechanical polishing smoothed particle hydrodynamics particulate flow rough pad wafer defects abrasive concentration
2014/10/10
In this paper, the mechanisms of material removal in chemical mechanical polishing (CMP) processes are investigated in detail by the smoothed particle hydrodynamics (SPH) method. The feature-scale beh...
Extended BIC for linear regression models with diverging number of relevant features and high or ultra-high feature spaces
Diverging number of parameters Feature selection Extended Bayes information criterion High dimensional feature space
2011/9/5
Abstract: In many conventional scientific investigations with high or ultra-high dimensional feature spaces, the relevant features, though sparse, are large in number compared with classical statistic...
Safe Feature Elimination in Sparse Supervised Learning
Sparse classi cation sparse regression LASSO feature elimination
2010/12/16
We investigate fast methods that allow to quickly eliminate variables (features) in supervised
learning problems involving a convex loss function and a l1-norm penalty, leading to a potentially subst...