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Pattern Recognition, ISSN 0031-3203, 2010, Volume 43, Issue 1, pp. 5 - 13
Searching for an optimal feature subset from a high dimensional feature space is known to be an NP-complete problem. We present a hybrid algorithm, SAGA, for... 
Dimensionality reduction | Feature subset selection | Curse of dimensionality | High dimensionality | SUPPORT VECTOR MACHINES | CANCER CLASSIFICATION | SEARCH | RELEVANCE | ANT COLONY OPTIMIZATION | ALGORITHM | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Neural networks | Mathematical optimization | Algorithms
Journal Article
Information Sciences, ISSN 0020-0255, 06/2019, Volume 486, pp. 393 - 418
The Column Subset Selection Problem is a hard combinatorial optimization problem that provides a natural framework for unsupervised feature selection, and... 
Feature selection | Unsupervised learning | Column subset selection | REGRESSION | MATRIX | UNSUPERVISED FEATURE-SELECTION | COMPUTER SCIENCE, INFORMATION SYSTEMS | ALGORITHMS | Algorithms
Journal Article
Information Sciences, ISSN 0020-0255, 2008, Volume 178, Issue 18, pp. 3577 - 3594
Feature subset selection is viewed as an important preprocessing step for pattern recognition, machine learning and data mining. Most of researches are focused... 
Categorical feature | Feature selection | Heterogeneous feature | Numerical feature | Rough sets | Neighborhood | rough sets | APPROXIMATION | ALGORITHM | COMPUTER SCIENCE, INFORMATION SYSTEMS | CLASSIFICATION | GRANULATION | heterogeneous feature | CLASSIFIERS | REDUCTION | categorical feature | FUZZY-LOGIC | numerical feature | SYSTEMS | neighborhood | feature selection
Journal Article
IEEE Transactions on Knowledge and Data Engineering, ISSN 1041-4347, 01/2013, Volume 25, Issue 1, pp. 1 - 14
Journal Article
Artificial Intelligence, ISSN 0004-3702, 1997, Volume 97, Issue 1, pp. 273 - 324
In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset of features upon which to focus its... 
Wrapper | Feature selection | Filter | Classification | filter | LEARNING ALGORITHMS | IRRELEVANT | wrapper | classification | feature selection | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Knowledge-Based Systems, ISSN 0950-7051, 11/2016, Volume 111, pp. 173 - 179
Rough set theory has been extensively discussed in machine learning and pattern recognition. It provides us another important theoretical tool for feature... 
Fuzzy neighborhood | Feature selection | Fuzzy decision | Rough set model | ATTRIBUTE REDUCTION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Analysis | Algorithms | Machine learning
Journal Article
Neurocomputing, ISSN 0925-2312, 01/2015, Volume 147, Issue 1, pp. 271 - 279
Feature selection is an important task for data analysis and information retrieval processing, pattern classification systems, and data mining applications. It... 
Wrapper | Binary ACO | Feature selection | Ant colony optimization (ACO) | Classification | PARTICLE SWARM OPTIMIZATION | NEURAL-NETWORKS | HYBRID GENETIC ALGORITHM | ANT COLONY OPTIMIZATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Information storage and retrieval | Electrical engineering | Algorithms | Data mining | Mathematical optimization | Analysis
Journal Article
Pattern Recognition, ISSN 0031-3203, 11/2004, Volume 37, Issue 11, pp. 2165 - 2176
Journal Article
Journal Article
SIAM Journal on Matrix Analysis and Applications, ISSN 0895-4798, 2013, Volume 34, Issue 4, pp. 1464 - 1499
We study the following problem of subset selection for matrices: given a matrix X is an element of R-nxm (m > n) and a sampling parameter k (n <= k <= m),... 
Feature selection | Volume sampling | Sparse approximation | Low-rank approximations | Low-stretch spanning trees | Subset selection | K-means clustering | low-stretch spanning trees | volume sampling | subset selection | MATHEMATICS, APPLIED | k-means clustering | low-rank approximations | APPROXIMATION | sparse approximation | RANK | ALGORITHMS | feature selection
Journal Article
Image and Vision Computing, ISSN 0262-8856, 08/2013, Volume 31, Issue 8, pp. 580 - 591
In this paper, we tackle the problem of gait recognition based on the model-free approach. Numerous methods exist; they all lead to high dimensional feature... 
Feature selection | Random forest | Model-free | Panoramic | Gait recognition | COMPUTER SCIENCE, SOFTWARE ENGINEERING | IMAGE | SYMMETRY | COMPUTER SCIENCE, THEORY & METHODS | OPTICS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Forests | Algorithms | Searching | Space probes | Classification | Strategy | Masks
Journal Article
Neurocomputing, ISSN 0925-2312, 11/2015, Volume 168, pp. 706 - 718
Conventional mutual information (MI) based feature selection (FS) methods are unable to handle heterogeneous feature subset selection properly because of data... 
Feature subset selection | Feature transformation | Heterogeneous features | Mutual information | DIMENSIONALITY REDUCTION | DISCRETIZATION | SEARCH | ALGORITHM | HISTOGRAM | CLASSIFICATION | SIMILARITY |