Large Tree Classifier with Heuristic Search and Global Training
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparative Analysis of Methods for Pruning Decision Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Globally Optimal Fuzzy Decision Trees for Classification and Regression
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Data Mining and Knowledge Discovery
The Application of Semantic Classification Trees to Natural Language Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel feature extraction method and hybrid tree classification for handwritten numeral recognition
Pattern Recognition Letters
Induction of Rules Subject to a Quality Constraint: Probabilistic Inductive Learning
IEEE Transactions on Knowledge and Data Engineering
Backpropagation in Decision Trees for Regression
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Heuristics for Hierarchical Partitioning with Application to Model Checking
CHARME '01 Proceedings of the 11th IFIP WG 10.5 Advanced Research Working Conference on Correct Hardware Design and Verification Methods
Double random field models for remote sensing image segmentation
Pattern Recognition Letters
Simplifying decision trees: A survey
The Knowledge Engineering Review
Segment choice models: feature-rich models for global distortion in statistical machine translation
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
A UNIFIED APPROACH TO GRAPHEME-TO-PHONEME CONVERSION FOR THE PLATTOS SLOVENIAN TEXT-TO-SPEECH SYSTEM
Applied Artificial Intelligence
An optimal QoS-based Web service selection scheme
Information Sciences: an International Journal
A hybrid method for robust car plate character recognition
Engineering Applications of Artificial Intelligence
Switching class labels to generate classification ensembles
Pattern Recognition
Learning speech semantics with keyword classification trees
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Pareto-optimality of oblique decision trees from evolutionary algorithms
Journal of Global Optimization
Learning with data streams – an NNTree based approach
EUC'05 Proceedings of the 2005 international conference on Embedded and Ubiquitous Computing
Risk bounds for CART classifiers under a margin condition
Pattern Recognition
Crucial combinations of parts for handwritten alphanumeric characters
Mathematical and Computer Modelling: An International Journal
Ensemble-based noise detection: noise ranking and visual performance evaluation
Data Mining and Knowledge Discovery
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A critical issue in classification tree design-obtaining right-sized trees, i.e. trees which neither underfit nor overfit the data-is addressed. Instead of stopping rules to halt partitioning, the approach of growing a large tree with pure terminal nodes and selectively pruning it back is used. A new efficient iterative method is proposed to grow and prune classification trees. This method divides the data sample into two subsets and iteratively grows a tree with one subset and prunes it with the other subset, successively interchanging the roles of the two subsets. The convergence and other properties of the algorithm are established. Theoretical and practical considerations suggest that the iterative free growing and pruning algorithm should perform better and require less computation than other widely used tree growing and pruning algorithms. Numerical results on a waveform recognition problem are presented to support this view.