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Inductive Learning Methods for Knowledge-Based Decision Support: A Comparative Analysis

https://doi.org/10.1007/bf00436712
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What this work says

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

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A Mathematical Theory of Communication
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Prediction and Entropy of Printed English
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Machine Learning
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Learning by Analogy: Formulating and Generalizing Plans from Past Experience
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Learning Decision Lists
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A General Framework for Induction and a Study of Selective Induction
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Induction of Decision Trees
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Interactive transfer of expertise: Acquisition of new inference rules
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A new basis for state-space learning systems and a successful implementation
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Machine learning: An artificial intelligence approach
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A theory and methodology of inductive learning
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Applying inductive learning to enhance knowledge-based expert systems
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OPERATIONALIZING MODELING KNOWLEDGE IN TERMS OF PREDICATE CALCULUS
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Bias, Version Spaces and Valiant's Learning Framework
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Eurisko: A program that learns new heuristics and domain concepts
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Feature discovery by competitive learning
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Explanation-Based Generalization: A Unifying View
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Concept learning: An information processing problem.
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Neural networks and physical systems with emergent collective computational abilities.
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FINDING SYNERGY BETWEEN DECISION SUPPORT SYSTEMS AND EXPERT SYSTEMS RESEARCH
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PREDICTING INDUSTRIAL BOND RATINGS WITH A PROBIT MODEL AND FUNDS FLOW COMPONENTS
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Some Studies in Machine Learning Using the Game of Checkers. II—Recent Progress
inferredcites →https://doi.org/10.1207/s15516709cog0901_5openalex-snapshot
Feature Discovery by Competitive Learning*
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Inducing Rules for Expert System Development: An Example Using Default and Bankruptcy Data
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Classification and Regression Trees.
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Classifying Bankrupt Firms with Funds Flow Components
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Classification and Regression Trees.
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Using an Expert System with Inductive Learning to Evaluate Business Loans

What points at this work

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

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Information-Based Dynamic Manufacturing System Scheduling
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Knowledge acquisition from an incomplete domain theory ? An application on the Stock Market
inferred← citeshttps://doi.org/10.1016/0306-4573(95)00015-9openalex-snapshot
The hybrid application of an inductive learning method and a neural network for intelligent information retrieval
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The micro-foundations of industrial diversification through foreign acquisitions: The multifaceted role of CEO experience
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Identifying route selection strategies in offshore emergency situations using decision trees
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Information-Based Dynamic Manufacturing System Scheduling
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DKAS: A Distributed Knowledge Acquisition System in a DSS
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Evolving Bayesian classifiers for credit control—a comparison with other machine-learning methods
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Learning-based scheduling in a flexible manufacturing flow line
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Inductive learning for risk classification
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Adaptive scheduling in dynamic flexible manufacturing systems: a dynamic rule selection approach
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A majority rules approach to data mining
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A Scalable Classification Algorithm for Very Large Datasets
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A Comparison of Neural Network and Expert Systems Algorithms with Common Multivariate Procedures for Analysis of Social Science Data
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Using Inductive Learning to Predict Bankruptcy
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