CSC '92 Proceedings of the 1992 ACM annual conference on Communications
On Piecewise-Linear Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Symbolic Representation of Neural Networks
Computer - Special issue: neural computing: companion issue to Spring 1996 IEEE Computational Science & Engineering
An Exact Probability Metric for Decision Tree Splitting and Stopping
Machine Learning
Forgetting Exceptions is Harmful in Language Learning
Machine Learning - Special issue on natural language learning
Combining the Perceptron Algorithm with Logarithmic Simulated Annealing
Neural Processing Letters
A Recency Inference Engine for Connectionist Knowledge Bases
Applied Intelligence
On Comparing Classifiers: Pitfalls toAvoid and a Recommended Approach
Data Mining and Knowledge Discovery
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Data Mining and Knowledge Discovery
A Survey of Methods for Scaling Up Inductive Algorithms
Data Mining and Knowledge Discovery
RainForest—A Framework for Fast Decision Tree Construction of Large Datasets
Data Mining and Knowledge Discovery
Effective Data Mining Using Neural Networks
IEEE Transactions on Knowledge and Data Engineering
An Implementation of Logical Analysis of Data
IEEE Transactions on Knowledge and Data Engineering
Guest Editor's Introduction: Applications of Machine Learning
IEEE Expert: Intelligent Systems and Their Applications
IEEE Expert: Intelligent Systems and Their Applications
RainForest - A Framework for Fast Decision Tree Construction of Large Datasets
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Rule Reduction over Numerical Attributes in Decision Tree Using Multilayer Perceptron
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Feature Selection for Meta-learning
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Feature Transformation and Multivariate Decision Tree Induction
DS '98 Proceedings of the First International Conference on Discovery Science
NeuroRule: A Connectionist Approach to Data Mining
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Extracting decision trees from trained neural networks
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining tasks and methods: scalability
Handbook of data mining and knowledge discovery
Connectionist and evolutionary models for learning, discovering and forecasting software effort
Managing data mining technologies in organizations
A comparative assessment of classification methods
Decision Support Systems
Tree induction vs. logistic regression: a learning-curve analysis
The Journal of Machine Learning Research
Disambiguating highly ambiguous words
Computational Linguistics - Special issue on word sense disambiguation
Computers and Operations Research
Interruptible anytime algorithms for iterative improvement of decision trees
UBDM '05 Proceedings of the 1st international workshop on Utility-based data mining
A comparison of machine learning with human judgment
Journal of Management Information Systems - Special section: Research in integrating learning capabilities into information systems
Pattern classification by concurrently determined piecewise linear and convex discriminant functions
Computers and Industrial Engineering - Special issue: Computational intelligence and information technology applications to industrial engineering selected papers from the 33 rd ICC&IE
Learning multicriteria fuzzy classification method PROAFTN from data
Computers and Operations Research
Anytime Learning of Decision Trees
The Journal of Machine Learning Research
Modeling the efficiency of top Arab banks: A DEA-neural network approach
Expert Systems with Applications: An International Journal
Construction of supervised and unsupervised learning systems for multilingual text categorization
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Pattern classification by concurrently determined piecewise linear and convex discriminant functions
Computers and Industrial Engineering
A neuro-computational intelligence analysis of the ecological footprint of nations
Computational Statistics & Data Analysis
An automated procedure for identifying poorly documented object oriented software components
C3S2E '09 Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering
Feedforward Neural Network with Multi-valued Connection Weights
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Any time induction of decision trees: an iterative improvement approach
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
A fast decision tree learning algorithm
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Modularity in inductively-learned word pronunciation systems
NeMLaP3/CoNLL '98 Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning
Do not forget: full memory in memory-based learning of word pronunciation
NeMLaP3/CoNLL '98 Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning
Learning the past tense of English verbs: the symbolic pattern associator vs. connectionist models
Journal of Artificial Intelligence Research
Induction of first-order decision lists: results on learning the past tense of English verbs
Journal of Artificial Intelligence Research
Understanding neural networks via rule extraction
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Reduced complexity rule induction
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
On learning algorithm selection for classification
Applied Soft Computing
A new computational intelligence technique based on human group formation
Expert Systems with Applications: An International Journal
Selecting and ranking time series models using the NOEMON approach
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Separation of data via concurrently determined discriminant functions
TAMC'07 Proceedings of the 4th international conference on Theory and applications of models of computation
Refinement of approximate domain theories by knowledge-based neural networks
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
Error-correcting output codes: a general method for improving multiclass inductive learning programs
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
Direct transfer of learned information among neural networks
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
Combining models from neural networks and inductive learning algorithms
Expert Systems with Applications: An International Journal
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
A neuro-computational intelligence analysis of the global consumer software piracy rates
Expert Systems with Applications: An International Journal
An investigation of TREPAN utilising a continuous oracle model
International Journal of Data Analysis Techniques and Strategies
Logarithmic simulated annealing for X-ray diagnosis
Artificial Intelligence in Medicine
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
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Despite the fact that many symbolic and neural network (connectionist) learning algorithms address the same problem of learning from classified examples, very little is known regarding their comparative strengths and weaknesses. Experiments comparing the ID3 symbolic learning algorithm with the perception and backpropagation neural learning algorithms have been performed using five large, real-world data sets. Overall, backpropagation performs slightly better than the other two algorithms in terms of classification accuracy on new examples, but takes much longer to train. Experimental results suggest that backpropagation can work significantly better on data sets containing numerical data. Also analyzed empirically are the effects of (1) the amount of training data, (2) imperfect training examples, and (3) the encoding of the desired outputs. Backpropagation occasionally outperforms the other two systems when given relatively small amounts of training data. It is slightly more accurate than ID3 when examples are noisy or incompletely specified. Finally, backpropagation more effectively utilizes a “distributed” output encoding.