搜索结果: 1-15 共查到“Feature Selection”相关记录24条 . 查询时间(0.088 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:How to capture tourists' search behavior in tourism forecasts?A two-stage feature selection approach
旅游预测 游客 搜索行为 两阶段 特征选择方法
2023/5/16
Hopfield Networks in Relevance and Redundancy Feature Selection Applied to Classification of Biomedical High-Resolution Micro-CT Images
feature selection image features pattern classification
2015/7/28
We study filter–based feature selection methods for classification of biomedical images. For feature selection, we use two filters — a relevance filter which measures usefulness of individual features...
Feature Selection Based on Term Frequency and T-Test for Text Categorization
feature selection term frequency t-test text classification
2013/6/14
Much work has been done on feature selection. Existing methods are based on document frequency, such as Chi-Square Statistic, Information Gain etc. However, these methods have two shortcomings: one is...
Greedy Feature Selection for Subspace Clustering
Subspace clustering unions of subspaces hybrid linear models sparse ap-proximation structured sparsity nearest neighbors low-rank approximation
2013/5/2
Unions of subspaces are powerful nonlinear signal models for collections of high-dimensional data. However, existing methods that exploit this structure require that the subspaces the signals of inter...
$l_{2,p}$ Matrix Norm and Its Application in Feature Selection
$l_{2,p}$ Matrix Norm Its Application Feature Selection
2013/5/2
Recently, $l_{2,1}$ matrix norm has been widely applied to many areas such as computer vision, pattern recognition, biological study and etc. As an extension of $l_1$ vector norm, the mixed $l_{2,1}$ ...
An iterative feature selection method for GRNs inference by exploring topological properties
SFS SFFS feature selection reverse-engineering gene networks inference systems biology bioinformatics
2011/10/9
Abstract: An important problem in bioinformatics is the inference of gene regulatory networks (GRN) from temporal expression profiles. In general, the main limitations faced by GRN inference methods i...
Sequential Lasso for feature selection with ultra-high dimensional feature space
extended BIC feature selection selection consistency Sequential Lasso
2011/7/19
We propose a novel approach, Sequential Lasso, for feature selection in linear regression models with ultra-high dimensional feature spaces.
Multi-stage Convex Relaxation for Feature Selection
Multi-stage Convex Relaxation Feature Selection
2011/7/5
A number of recent work studied the effectiveness of feature selection using Lasso. It is known that under the restricted isometry properties (RIP), Lasso does not generally lead to the exact recovery...
Optimal feature selection for 3D facial expression recognition using coarse-to-fine classification
3D facial expression recognition Fisher criterion-based approach using within group classification
2010/11/22
Automatic facial expression recognition for novel individuals from 3D face data is a challenging task in pattern analysis. This paper describes a feature selection process for pose-invariant 3D facial...
Using covariates for improving the minimum redundancy maximum relevance feature selection method
Mutual information mRMR unsupervised learning support vector machines SINBAD covariates
2010/11/22
Maximizing the joint dependency with a minimum size of variables is generally the main task of feature selection. For obtaining a minimal subset, while trying to maximize the joint dependency with the...
A Method for Avoiding Bias from Feature Selection with Application to Naive Bayes Classification Models
feature selection optimistic bias naive Bayes models gene expression data
2009/9/22
For many classication and regression problems, a large number of
features are available for possible use this is typical of DNA microarray data
on gene expression, for example. Often, for computatio...
LASSO, Iterative Feature Selection and the Correlation Selector: Oracle inequalities and numerical performances
Regression estimation statistical learning confidence regions shrinkage and thresholding methods LASSO
2009/9/16
We propose a general family of algorithms for regression estimation with quadratic loss, on the basis of geometrical considerations. These algorithms are able to select relevant functions into a large...
Feature selection in omics prediction problems using cat scores and false non-discovery rate control
Feature selection omics prediction problems cat scores false non-discovery rate control
2010/3/18
We revisit the problem of feature selection in linear discriminant analysis (LDA),
i.e. when features are correlated. First, we introduce a pooled centroids formulation
of the multi-class LDA predic...
AIRBORNE LIDAR FEATURE SELECTION FOR URBAN CLASSIFICATION USING RANDOM FORESTS
Lidar Full-waveform Classifi cation Feature selection Random Forests Urban scenes
2016/2/29
Various multi-echo and Full-waveform (FW) lidar features can be processed. In this paper, multiple classifers are applied to lidar
feature selection for urban scene classification. Random fores...
DRM: Dynamic Region Matching for Image Retrieval Using Probabilistic Fuzzy Matching and Boosting Feature Selection
Dynamic Region Matching Image Retrieval Probabilistic Fuzzy Matching
2010/12/17
This paper considers the semantic gap in content-based image retrieval from two aspects: (1)
irrelevant visual contents (e.g. background) scatter the mapping from image to human perception; (2) unsup...