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Symbolic and Neural Learning Algorithms: An Experimental Comparison
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Principles of Neurodynamics. Perceptrons and the Theory of Brain Mechanisms.
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Frank Rosenblatt: Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms
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LEARNING EFFICIENT CLASSIFICATION PROCEDURES AND THEIR APPLICATION TO CHESS END GAMES
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A Theory and Methodology of Inductive Learning
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On the Proper Treatment of Connectionism
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Knowledge Acquisition Via Incremental Conceptual Clustering
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International application of a new probability algorithm for the diagnosis of coronary artery disease
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Generalization as search
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A theory and methodology of inductive learning
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A parallel network that learns to play backgammon
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Connectionist learning procedures
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Connectionism and cognitive architecture: A critical analysis
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On the complexity of loading shallow neural networks
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Decision tree induction systems: A Bayesian analysis
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CONNECTIONIST LEARNING PROCEDURES11This chapter appeared in Volume 40 of Artificial Intelligence in 1989, reprinted with permission of North-Holland Publishing. It is a revised version of Technical Report CMU-CS-87-115, which has the same title and was prepared in June 1987 while the author was at…
inferredcites →https://doi.org/10.1016/b978-0-934613-03-3.50040-4openalex-snapshot
Generalization as Search
inferredcites →https://doi.org/10.1016/b978-0-934613-41-5.50007-6openalex-snapshot
DECISION TREES AS PROBABILISTIC CLASSIFIERS
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Experiments on the Costs and Benefits of Windowing in ID3
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Improved Decision Trees: A Generalized Version of ID3
inferredcites →https://doi.org/10.1016/b978-1-55860-036-2.50048-5openalex-snapshot
UNKNOWN ATTRIBUTE VALUES IN INDUCTION
inferredcites →https://doi.org/10.1016/b978-1-55860-036-2.50049-7openalex-snapshot
PROCESSING ISSUES IN COMPARISONS OF SYMBOLIC AND CONNECTIONIST LEARNING SYSTEMS
inferredcites →https://doi.org/10.1016/b978-1-55860-141-3.50007-9openalex-snapshot
A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping
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Simplifying decision trees
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On the proper treatment of connectionism
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On the proper treatment of the connection between connectionism and symbolism
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An Empirical Comparison of Pruning Methods for Decision Tree Induction
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Toward a Unified Science of Machine Learning
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Incremental Induction of Decision Trees
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Logic Design and Switching Theory
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Dynamic Node Creation in Backpropagation Networks
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Perceptron Trees: A Case Study in Hybrid Concept Representations
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Condor-a hunter of idle workstations
inferredcites →https://doi.org/10.1109/ijcnn.1989.118509openalex-snapshot
Dynamic node creation in backpropagation networks
inferredcites →https://doi.org/10.21236/ad0256582openalex-snapshot
PRINCIPLES OF NEURODYNAMICS. PERCEPTRONS AND THE THEORY OF BRAIN MECHANISMS
inferredcites →https://doi.org/10.21236/ada164453openalex-snapshot
Learning Internal Representations by Error Propagation
inferredcites →https://doi.org/10.2307/1419730openalex-snapshot
Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms
inferredcites →https://doi.org/10.2307/1423065openalex-snapshot
Explorations in Parallel Distributed Processing: A Handbook of Models, Programs, and Exercises
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Decision Tree Induction Systems: A Bayesian Analysis
inferredcites →https://doi.org/10.7551/mitpress/2103.001.0001openalex-snapshot
Connections and Symbols
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Learning and Relearning in Boltzmann Machines
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Connectionism and Cognitive Architecture: A Critical Analysis
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Parallel Distributed Processing
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Parallel Distributed Processing
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A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms
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A Recency Inference Engine for Connectionist Knowledge Bases
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Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
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On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach
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RainForest—A Framework for Fast Decision Tree Construction of Large Datasets
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A Survey of Methods for Scaling Up Inductive Algorithms
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Combining the Perceptron Algorithm with Logarithmic Simulated Annealing
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Very Simple Classification Rules Perform Well on Most Commonly Used Datasets
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Technical Note: Selecting a Classification Method by Cross-Validation
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Using an unsupervized neural network and decision tree as knowledge acquisition tools for FMS scheduling
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A Comparison of Machine Learning with Human Judgment
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A LEARNING-ENABLED INTEGRATIVE TRUST MODEL FOR E-MARKETS
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Connectionist Models for Learning, Discovering, and Forecasting Software Effort: An Empirical Study
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Combining Connectionist and Symbolic Learning to Refine Certainty Factor Rule Bases
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Survey of expert opinion: Which machine learning method may be used for which task?
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Computer-aided detection (CAD) of breast masses in mammography: combined detection and ensemble classification
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Inductive inference and neural nets
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Combination Approaches Improve Predictive Performance of Diagnostic Rules for Mass-Spectrometry Proteomic Data
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A Comparative Study of Classification Algorithms: Statistical, Machine Learning and Neural Network
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Epidemiologic Interpretation of Artificial Neural Networks
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Using Neural Networks to Identify Patients Unlikely to Achieve a Reduction in Bodily Pain After Total Hip Replacement Surgery
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A neuro‐computational intelligence analysis of the US retailers' efficiency
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Machine learning in control of functional electrical stimulation systems for locomotion
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Symbolic representation of neural networks
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Neural implementation of tree classifiers
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A learning process of the matching identification problem
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A connectionist approach to generating oblique decision trees
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A comparative study on heuristic algorithms for generating fuzzy decision trees
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Classification of multisensor remote-sensing images by structured neural networks
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Neural networks for classification: a survey
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Effective data mining using neural networks
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An implementation of logical analysis of data
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μARTMAP: use of mutual information for category reduction in Fuzzy ARTMAP
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Improving learning accuracy of fuzzy decision trees by hybrid neural networks
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Classification Models: Non Evolutionary vs. Evolutionary Approach
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Knowledge enhanced connectionist models for short-term electric load forecasting
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PID autotuner design using machine learning
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Can competitive learning compete? Comparing a connectionist clustering technique to symbolic approaches
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Building expert systems by training with automatic neural network generating ability
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2-D object recognition by structured neural networks in a pyramidal architecture
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Training A Neural Network By Simulation For Dispatching Problems
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Classification Algorithm Based on Human Social Behavior
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A method of processing unknown attribute values by ID3
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Eclectic rule extraction from Neural Networks using aggregated Decision Trees
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A Comparison Between Statistical and Symbolic Learning Approaches for Generative Policy Models
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Application of binary neural networks for classification
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ECOC-based structured neural networks
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An experimental comparison between ELM and C4.5 for classification problems with symbolic attributes
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Backpropagation learning on ribosomal binding sites in DNA sequences using preprocessed features
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Evolution versus training: an investigation into combining genetic algorithms and neural networks
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Assessing Wireless Network Dependability through Knowledge Extraction via Decision Trees
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Learning linear threshold functions
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A knowledge-based system for multiple pattern recognition paradigms support
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Interpolation, wavelet compression, and neural network analysis for hazardous waste characterization
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Extracting rules from a GA-pruned neural network
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Improving learning accuracy of fuzzy decision trees by hybrid neural networks
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Building algorithm profiles for prior model selection in knowledge discovery systems
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Why are neural networks sometimes much more accurate than decision trees: an analysis on a bio-informatics problem
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A majority rules approach to data mining
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Improving a phoneme classification neural network through problem decomposition
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Experiments with the cascade-correlation algorithm
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Growing layers of perceptrons: introducing the Extentron algorithm
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Dynamic neural networks with the use of divide and conquer
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SIR: simultaneous induction of rules using neural networks
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Constraining the MLP power of expression to facilitate symbolic rule extraction
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MicroARTMAP: use of mutual information for category reduction in fuzzy ARTMAP
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Finding relevant knowledge: KBCC applied to DNA splice-junction determination
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Transferring domain rules in a constructive network: introducing RBCC
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An approach for generalizing knowledge based on rules with priority orders
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