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AE1: An extension matrix approximate method for the general covering problem
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1016/0167-7136(83)90132-4openalex-snapshot
A theory and methodology of inductive learning
inferredcites →https://doi.org/10.1016/b978-0-08-051054-5.50008-xopenalex-snapshot
A THEORY AND METHODOLOGY OF INDUCTIVE LEARNING
inferredcites →https://doi.org/10.1016/b978-0-7204-0406-7.50022-3openalex-snapshot
variable-valued logic and its applications to pattern recognition and machine learning
inferredcites →https://doi.org/10.1016/s0022-0000(74)80044-9openalex-snapshot
Approximation algorithms for combinatorial problems
inferredcites →https://doi.org/10.1117/12.964180openalex-snapshot
An Extension Matrix Approach To The General Covering Problem
inferredcites →https://doi.org/10.13021/mars/3596openalex-snapshot
On the Quasi-Minimal Solution of the General Covering Problem
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Rule induction with extension matrices
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Mining Human Interpretable Knowledge with Fuzzy Modeling Methods: An Overview
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Neural Network Based Classifiers for a Vast Amount of Data
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Hybrid interpretation of induction results
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Accurate Decision Tree with Cost Constraints
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An Efficient Rules Induction Algorithm for Rough Set Classification
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Similarity-Based Feature Selection for Learning from Examples with Continuous Values
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Inductive learning: Algorithms and frontiers
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AECAM: An extension matrix algorithm on a cellular automata machine
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ICAS: An incremental concept acquisition system using attribute-based description
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FCV1: A new fast greedy covering algorithm
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The minimum feature subset selection problem
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A novel classification model for cotton yarn quality based on trained neural network using genetic algorithm
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Fuzzy feature selection based on min–max learning rule and extension matrix
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Delphi Inductive Algorithm Realization Based on the Statistical Theory
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A new approach to fuzzy rule generation: fuzzy extension matrix
inferred← citeshttps://doi.org/10.1080/10798587.2011.10643140openalex-snapshot
A Hybrid Method for Intrusion Detection With Ga-Based Feature Selection
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RIEVL: recursive induction learning in hand gesture recognition
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Fuzzy interpretation of discretized intervals
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Fast minimization of Boolean functions with high minimality
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PowerQuest: Trace Driven Data Mining for Power Optimization
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NP-Hard Problems of Learning from Examples
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A positive extension matrix algorithm/sub AE18/ of learning from examples
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Generation of Chinese prosodic phrasing rules by an extension matrix algorithm
inferred← citeshttps://doi.org/10.1109/icct.2012.6511313openalex-snapshot
An improved learning algorithm of decision tree based on entropy uncertainty deviation
inferred← citeshttps://doi.org/10.1109/icii.2001.983038openalex-snapshot
HGR: a new rule induction algorithm based on extension matrices
inferred← citeshttps://doi.org/10.1109/icmlc.2002.1174546openalex-snapshot
Research on algorithm of decision tree induction
inferred← citeshttps://doi.org/10.1109/icmlc.2004.1382129openalex-snapshot
Feature selection based on fuzzy extension matrix for multi-class problem
inferred← citeshttps://doi.org/10.1109/icmlc.2006.258658openalex-snapshot
A Kind of Inductive Learning Classification Algorithm Based on Statistics Rule
inferred← citeshttps://doi.org/10.1109/icmlc.2006.258973openalex-snapshot
Selection of Parameters Based on Fuzzy Extension Matrix
inferred← citeshttps://doi.org/10.1109/icsmc.1999.823231openalex-snapshot
A problem of selecting optimal subset of fuzzy-valued features
inferred← citeshttps://doi.org/10.1109/icsmc.1999.823356openalex-snapshot
Recognition rule acquisition by an advanced extension matrix algorithm
inferred← citeshttps://doi.org/10.1109/icsmc.2000.884415openalex-snapshot
An extension matrix approach to Chinese character recognition
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Rule learning based on neural network ensemble
inferred← citeshttps://doi.org/10.1109/isise.2010.153openalex-snapshot
Attribute Reduction Algorithm and the Generation of Hybrid Decision Tree Based on Discernibility Matrix in Rough Set
inferred← citeshttps://doi.org/10.1109/tai.1995.479514openalex-snapshot
Noise handling with extension matrices
inferred← citeshttps://doi.org/10.1109/tai.2002.1180804openalex-snapshot
Dynamic refinement of classification rules
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Adaptive Fuzzy Consensus Clustering Framework for Clustering Analysis of Cancer Data
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PARAMETERS OPTIMIZE METHOD BASED ON GENETIC AND SIMULATED ANNEALING ALGORITHMS
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Building Intelligent Learning Database Systems
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IBA-II: Another Item-Based Algorithm of Learning from Examples
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Interactive presentation: PowerQuest: trace driven data mining for power optimization
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