Machine learning: applications in expert systems and information retrieval
Machine learning: applications in expert systems and information retrieval
Information Processing Letters
Inductive knowledge acquisition: a case study
Proceedings of the Second Australian Conference on Applications of expert systems
International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
The cascade-correlation learning architecture
Advances in neural information processing systems 2
On estimating probabilities in tree pruning
EWSL-91 Proceedings of the European working session on learning on Machine learning
Computational learning theory: an introduction
Computational learning theory: an introduction
Digital engineering design: a modern approach
Digital engineering design: a modern approach
C4.5: programs for machine learning
C4.5: programs for machine learning
Cost-sensitive pruning of decision trees
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
The Quadtree and Related Hierarchical Data Structures
ACM Computing Surveys (CSUR)
Decision Tree Induction Based on Efficient Tree Restructuring
Machine Learning
A Function-Based Classifier Learning Scheme Using Genetic Programming
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Influential Rule Search Scheme (IRSS)-A New Fuzzy Pattern Classifier
IEEE Transactions on Knowledge and Data Engineering
Computer Vision and Image Understanding
Variations of the two-spiral task
Connection Science
Expert Systems with Applications: An International Journal
Computer Vision and Image Understanding
Medical Diagnosis System of Breast Cancer Using FCM Based Parallel Neural Networks
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Performance comparison between backpropagation, neuro-fuzzy network, and SVM
CSR'06 Proceedings of the First international computer science conference on Theory and Applications
Tensor scale: An analytic approach with efficient computation and applications
Computer Vision and Image Understanding
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In this paper we propose a rule-based inductive learning algorithm called Multiscale Classification (MSC). It can be applied to any N-dimensional real or binary classification problem to classify the training data by successively splitting the feature space in half. The algorithm has several significant differences from existing rule-based approaches: learning is incremental, the tree is non-binary, and backtracking of decisions is possible to some extent.The paper first provides background on current machine learning techniques and outlines some of their strengths and weaknesses. It then describes the MSC algorithm and compares it to other inductive learning algorithms with particular reference to ID3, C4.5, and back-propagation neural networks. Its performance on a number of standard benchmark problems is then discussed and related to standard learning issues such as generalization, representational power, and over-specialization.