Reference health

Adaptive, Hybrid Feature Selection (AHFS)

https://doi.org/10.1016/j.patcog.2021.107932
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22/22 checkable references clean · checked 2026-07-25

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

13 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 22 checked references that resolve
resolves10.1016/j.patcog.2019.107077
Informative variable identifier: Expanding interpretability in feature selection
resolves10.1016/j.patcog.2019.03.026
Local discriminative based sparse subspace learning for feature selection
resolves10.1016/j.patcog.2019.04.020
Nonnegative Laplacian embedding guided subspace learning for unsupervised feature selection
resolves10.1016/j.patrec.2014.07.004
Structured multi-class feature selection with an application to face recognition
resolves10.1016/j.compag.2015.10.017
mRMR-based feature selection for classification of cotton foreign matter using hyperspectral imaging
resolves10.1016/j.ymssp.2014.12.021
Multisensor-based real-time quality monitoring by means of feature extraction, selection and modeling for Al alloy in arc welding
resolves10.1016/j.neucom.2011.03.043
Feature selection for high-dimensional machinery fault diagnosis data using multiple models and Radial Basis Function networks
resolves10.1016/j.apenergy.2015.08.102
Comparison of feature selection methods using ANNs in MCP-wind speed methods. A case study
resolves10.1016/j.neucom.2014.09.090
Wind speed prediction using reduced support vector machines with feature selection
resolves10.1016/j.patcog.2020.107525
Mutual information based feature subset selection in multivariate time series classification
resolves10.1016/j.ipl.2015.07.005
Efficient feature selection based on correlation measure between continuous and discrete features
resolves10.1016/j.ymssp.2016.12.040
A fault diagnosis scheme for planetary gearboxes using modified multi-scale symbolic dynamic entropy and mRMR feature selection
resolves10.1016/j.patcog.2019.02.016
Simultaneous feature selection and discretization based on mutual information
resolves10.1016/j.jnca.2011.01.002
Mutual information-based feature selection for intrusion detection systems
resolves10.1109/72.298224
Using mutual information for selecting features in supervised neural net learning
resolves10.1016/j.neucom.2015.11.074
A fault diagnosis approach for diesel engines based on self-adaptive WVD, improved FCBF and PECOC-RVM
resolves10.1613/jair.3831
A Feature Subset Selection Algorithm Automatic Recommendation Method
resolves10.1007/BF02478259
A logical calculus of the ideas immanent in nervous activity
resolves10.1561/2000000039
Deep Learning: Methods and Applications
resolves10.1016/j.patcog.2019.04.011
Robust Jointly Sparse Regression with Generalized Orthogonal Learning for Image Feature Selection
resolves10.1016/j.patcog.2020.107517
Accelerating information entropy-based feature selection using rough set theory with classified nested equivalence classes
resolves10.1016/j.jbi.2018.07.014
Relief-based feature selection: Introduction and review
The 13 references without a DOI — listed, not checked
no DOI — not checkedAn introduction to variable and feature selection
no DOI — not checkedA review paper on feature selection methodologies and their applications
no DOI — not checked10.1016/j.patcog.2021.107932_bib0014
no DOI — not checkedModified mutual information-based feature selection for intrusion detection systems in decision tree learning
no DOI — not checked10.1016/j.patcog.2021.107932_bib0020
no DOI — not checked10.1016/j.patcog.2021.107932_bib0023
no DOI — not checked10.1016/j.patcog.2021.107932_bib0024
no DOI — not checked10.1016/j.patcog.2021.107932_bib0025
no DOI — not checkedAutomatic generation a net of models for high and low levels of production control
no DOI — not checked10.1016/j.patcog.2021.107932_bib0028
no DOI — not checkedDiagnostics of wind turbines based on incomplete sensor data
no DOI — not checked10.1016/j.patcog.2021.107932_bib0031
no DOI — not checkedM. Lichman, UCI machine learning repository, 2013, http://archive.ics.uci.edu/ml.
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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