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A monotonic measure for optimal feature selection

https://doi.org/10.1007/bfb0026678
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-4615-2736-7_9openalex-snapshot
SNNS (Stuttgart Neural Network Simulator)
inferredcites →https://doi.org/10.1016/b978-1-55860-335-6.50023-4openalex-snapshot
Irrelevant Features and the Subset Selection Problem
inferredcites →https://doi.org/10.1016/s0169-7161(82)02038-0openalex-snapshot
35 Use of distance measures, information measures and error bounds in feature evaluation
inferredcites →https://doi.org/10.1109/tc.1977.1674939openalex-snapshot
A Branch and Bound Algorithm for Feature Subset Selection
inferredcites →https://doi.org/10.1142/s0218001488000145openalex-snapshot
ON AUTOMATIC FEATURE SELECTION

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Sensitive three‐dimensional ultrasound assessment of carotid atherosclerosis by weighted average of local vessel wall and plaque thickness change
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Feature Selection Method Using Preferences Aggregation
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Feature Selection in an Electric Billing Database Considering Attribute Inter-dependencies
inferred← citeshttps://doi.org/10.1007/3-540-45571-x_12openalex-snapshot
Consistency Based Feature Selection
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Feature Selection Using Consistency Measure
inferred← citeshttps://doi.org/10.1007/978-1-4615-5689-3_4openalex-snapshot
Feature Selection Methods
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Developing Classification Techniques from Biological Databases Using Simulated Annealing
inferred← citeshttps://doi.org/10.1007/978-3-030-86534-4_23openalex-snapshot
Filter-Based Feature Selection Methods for Industrial Sensor Data: A Review
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A Scalable Feature Selection Algorithm for Large Datasets – Quick Branch & Bound Iterative (QBB-I)
inferred← citeshttps://doi.org/10.1007/978-3-319-10247-4_7openalex-snapshot
Feature Selection
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Data Reduction for Pattern Recognition and Data Analysis
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Machine Learning: ECML-98
inferred← citeshttps://doi.org/10.1007/bfb0095273openalex-snapshot
Hybrid search of feature subsets
inferred← citeshttps://doi.org/10.1007/s10844-007-0037-0openalex-snapshot
Consistency measures for feature selection
inferred← citeshttps://doi.org/10.1016/j.aej.2022.11.002openalex-snapshot
Relevance-diversity algorithm for feature selection and modified Bayes for prediction
inferred← citeshttps://doi.org/10.1016/j.camwa.2013.05.033openalex-snapshot
Feature selection filter for classification of power system operating states
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An optimization of ReliefF for classification in large datasets
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Synergies between operations research and data mining: The emerging use of multi-objective approaches
inferred← citeshttps://doi.org/10.1016/j.eswa.2018.04.033openalex-snapshot
Generation of compound features based on feature interaction for classification
inferred← citeshttps://doi.org/10.1016/j.eswa.2020.113398openalex-snapshot
Markov blanket-based universal feature selection for classification and regression of mixed-type data
inferred← citeshttps://doi.org/10.1016/j.eswa.2020.113971openalex-snapshot
An efficient multivariate feature ranking method for gene selection in high-dimensional microarray data
inferred← citeshttps://doi.org/10.1016/j.knosys.2007.07.001openalex-snapshot
Mixed feature selection based on granulation and approximation
inferred← citeshttps://doi.org/10.1016/j.knosys.2011.01.005openalex-snapshot
One Dependence Value Difference Metric
inferred← citeshttps://doi.org/10.1016/s0004-3702(03)00079-1openalex-snapshot
Consistency-based search in feature selection
inferred← citeshttps://doi.org/10.1016/s0167-8655(01)00019-8openalex-snapshot
Information-theoretic algorithm for feature selection
inferred← citeshttps://doi.org/10.1016/s0957-4174(98)90049-5openalex-snapshot
Some issues on scalable feature selection1This is an extended version of the paper presented at the Fourth World Congress of Expert Systems: Application of Advanced Information Technologies held in Mexico City in March 1998.1
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Finding Essential Attributes from Binary Data
inferred← citeshttps://doi.org/10.1063/5.0296249openalex-snapshot
Using the RFC_PSO hybrid algorithm in sorting informative features
inferred← citeshttps://doi.org/10.1088/0031-9155/58/17/5959openalex-snapshot
Novel 3D ultrasound image-based biomarkers based on a feature selection from a 2D standardized vessel wall thickness map: a tool for sensitive assessment of therapies for carotid atherosclerosis
inferred← citeshttps://doi.org/10.1088/0957-0233/27/5/055501openalex-snapshot
Hyperspectral band selection based on consistency-measure of neighborhood rough set theory
inferred← citeshttps://doi.org/10.1109/aiccsa47632.2019.9035281openalex-snapshot
Fundamentals of Feature Selection: An Overview and Comparison
inferred← citeshttps://doi.org/10.1109/bigdata.2015.7363742openalex-snapshot
Super-CWC and super-LCC: Super fast feature selection algorithms
inferred← citeshttps://doi.org/10.1109/iccci.2015.7218098openalex-snapshot
A comparative study of various feature selection techniques in high-dimensional data set to improve classification accuracy
inferred← citeshttps://doi.org/10.1109/icdm.2002.1183917openalex-snapshot
Feature selection algorithms: a survey and experimental evaluation
inferred← citeshttps://doi.org/10.1109/iiai-aai.2017.61openalex-snapshot
Iterative Feature Selection Based on Binary Consistency
inferred← citeshttps://doi.org/10.1109/iot-siu.2019.8777483openalex-snapshot
Filtering spam messages and mails using fuzzy C means algorithm
inferred← citeshttps://doi.org/10.1109/issnip.2004.1417497openalex-snapshot
Constructing Personalized Catalogs for Speech-Enabled Applications
inferred← citeshttps://doi.org/10.1109/smc.2013.735openalex-snapshot
Fuzzy Consistency Measure with Particle Swarm Optimization for Feature Selection
inferred← citeshttps://doi.org/10.1109/tkde.2005.66openalex-snapshot
Toward integrating feature selection algorithms for classification and clustering
inferred← citeshttps://doi.org/10.1109/tnn.2004.841414openalex-snapshot
Estimating Optimal Feature Subsets Using Efficient Estimation of High-Dimensional Mutual Information
inferred← citeshttps://doi.org/10.1109/tpami.2004.28openalex-snapshot
Fast branch & bound algorithms for optimal feature selection
inferred← citeshttps://doi.org/10.1109/tsmcb.2003.817106openalex-snapshot
Relevant, Irredundant Feature Selection and Noisy Example Elimination
inferred← citeshttps://doi.org/10.1111/coin.12072openalex-snapshot
A Fast and Accurate Feature Selection Algorithm Based on Binary Consistency Measure
inferred← citeshttps://doi.org/10.1142/s0218001406004831openalex-snapshot
BIOMETRIC WRITER IDENTIFICATION: FEATURE ANALYSIS AND CLASSIFICATION
inferred← citeshttps://doi.org/10.1631/jzus.2004.1382openalex-snapshot
Feature selection based on mutual information and redundancy-synergy coefficient
inferred← citeshttps://doi.org/10.20944/preprints202505.1442.v1openalex-snapshot
Outsourced Privacy-Preserving Feature Selection Based on Fully Homomorphic Encryption
inferred← citeshttps://doi.org/10.25518/0037-9565.5694openalex-snapshot
A Framework for Categorize Feature Selection Algorithms for Classification and Clustering
inferred← citeshttps://doi.org/10.25959/23240009openalex-snapshot
Novel feature selection algorithms for improving neural network performance
inferred← citeshttps://doi.org/10.3233/ida-2009-0364openalex-snapshot
Searching for interacting features in subset selection1
inferred← citeshttps://doi.org/10.32657/10356/48641openalex-snapshot
Robust feature selection for high-dimensional and small-sized gene expression data
inferred← citeshttps://doi.org/10.3389/fphys.2018.01767openalex-snapshot
Fractal and Multifractal Properties of Electrographic Recordings of Human Brain Activity: Toward Its Use as a Signal Feature for Machine Learning in Clinical Applications
inferred← citeshttps://doi.org/10.3390/a15070229openalex-snapshot
Privacy-Preserving Feature Selection with Fully Homomorphic Encryption
inferred← citeshttps://doi.org/10.3390/info8040159openalex-snapshot
sCwc/sLcc: Highly Scalable Feature Selection Algorithms
inferred← citeshttps://doi.org/10.3390/make4010007openalex-snapshot
A Novel Framework for Fast Feature Selection Based on Multi-Stage Correlation Measures
inferred← citeshttps://doi.org/10.48550/arxiv.1101.2320openalex-snapshot
Review and Evaluation of Feature Selection Algorithms in Synthetic Problems
inferred← citeshttps://doi.org/10.5120/8642-2463openalex-snapshot
Radial Basis Function (RBF) Neural Network Classification based on Consistency Evaluation Measure
inferred← citeshttps://doi.org/10.5220/0003093204540457openalex-snapshot
INTERLEAVING FORWARD BACKWARD FEATURE SELECTION
inferred← citeshttps://doi.org/10.52731/iee.v5.i1.262openalex-snapshot
Iterative Consistency-Based Feature Selection and Its Application to Nucleotide Sequences of Influenza A Viruses
inferred← citeshttps://doi.org/10.5815/ijmecs.2013.12.05openalex-snapshot
Spam Mail Detection through Data Mining – A Comparative Performance Analysis
inferred← citeshttps://doi.org/10.6029/smartcr.2014.03.007openalex-snapshot
Feature Selection: A literature Review
inferred← citeshttps://doi.org/10.7287/peerj-cs.76v0.1/reviews/1openalex-snapshot
Peer Review #1 of "Complexity curve: a graphical measure of data complexity and classifier performance (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.76v0.1/reviews/2openalex-snapshot
Peer Review #2 of "Complexity curve: a graphical measure of data complexity and classifier performance (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.76v0.1/reviews/3openalex-snapshot
Peer Review #3 of "Complexity curve: a graphical measure of data complexity and classifier performance (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.76v0.2/reviews/1openalex-snapshot
Peer Review #1 of "Complexity curve: a graphical measure of data complexity and classifier performance (v0.2)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.76v0.2/reviews/2openalex-snapshot
Peer Review #2 of "Complexity curve: a graphical measure of data complexity and classifier performance (v0.2)"
inferred← citeshttps://doi.org/10.7717/peerj-cs.76openalex-snapshot
Complexity curve: a graphical measure of data complexity and classifier performance
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.