An Introduction to Variable and Feature Selection
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Summary
The contributions of this special issue cover a wide range of aspects of variable and feature selection: providing a better understanding of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.
- Type
- article
- Published
- 2003-01-01
- Cited by
- 16,967
- References
- 51
- OpenAlex
- https://openalex.org/W7066667914
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:379259
Keywords
Feature selection, Feature (linguistics), Variable (mathematics), Focus (optics), Pattern recognition (psychology)
References
- Pattern Classification
- A New Metric-Based Approach to Model Selection
- Bayesian Input Variable Selection Using Posterior Probabilities and Expected Utilities
- Selection of Relevant Features and Examples in Machine Learning
- On Feature Selection: Learning with Exponentially Many Irrelevant Features as Training Examples
- Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection
- Learning with Kernels: support vector machines, regularization, optimization, and beyond
- Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space
- Toward Optimal Feature Selection
- Withdrawing an example from the training set: An analytic estimation of its effect on a non-linear parameterised model
- The Elements of Statistical Learning
- On the Approximability of Minimizing Nonzero Variables or Unsatisfied Relations in Linear Systems
- A training algorithm for optimal margin classifiers
- Feature Selection for SVMs
- Benefitting from the Variables that Variable Selection Discards
- Support vector machine classification and validation of cancer tissue samples using microarray expression data
- Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
- Adaptive Scaling for Feature Selection in SVMs
- Optimal Brain Damage
- Dimensionality Reduction via Sparse Support Vector Machines
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- A modular architecture for systematic text categorisation
- Vibration, Buckling and Dynamic Stability of Stepped Beams with Multiple Transverse Cracks
- Software defect prediction using static code metrics : formulating a methodology
- Interpretation of gene expression microarray experiments
- Some studies on the load carrying capacity of shallow foundation resting over geogrid-reinforced sand under eccentric load
- Sélection des variables informatives pour l'apprentissage supervisé multi-tables
- Exploring Characteristics of Code Churn
- Modeling Lapse Rates:Investigating the Variables That Drive Lapse Rates
- Algorithmes métaheuristiques hybrides pour la sélection de gènes et la classification de données de biopuces. (Hybrid metaheuristics algorithms for gene selection and classification of microarray data)
- Machine Learning for First-Order Theorem Proving
- Edge cross-section profile for colonoscopic object detection
- Semi-supervised Feature Selection via Spectral Analysis
- A user's guide to support vector machines.
- A Novel Distinguishability Based Weighted Feature Selection Algorithms for Improved Classification of Gene Microarray Dataset
- INFORMATION-VALUE-BASED FEATURE SELECTION ALGORITHM FOR ANOMALY DETECTION OVER DATA STREAMS
- Advances in dissimilarity-based data visualisation
- A machine learning perspective on the development of clinical decision support systems utilizing mass spectra of blood samples
- Ranking analysis of microarray data: a powerful method for identifying differentially expressed genes.
- Inverse retinotopy: Inferring the visual content of images from brain activation patterns
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