Improved boosting algorithms using confidence-rated predictions
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Using output codes to boost multiclass learning problems
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
The Alternating Decision Tree Learning Algorithm
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Option Decision Trees with Majority Votes
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Combining Subclassifiers in Text Categorization: A DST-Based Solution and a Case Study
IEEE Transactions on Knowledge and Data Engineering
A Wrapper Method for Feature Selection in Multiple Classes Datasets
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Rotation-based model trees for classification
International Journal of Data Analysis Techniques and Strategies
Learning multi-label alternating decision trees from texts and data
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
Complex feature alternating decision tree
International Journal of Intelligent Systems Technologies and Applications
Expert Systems with Applications: An International Journal
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
Advanced Engineering Informatics
Engineering Applications of Artificial Intelligence
An approach for web service discoverability anti-pattern detection for journal of web engineering
Journal of Web Engineering
Supervised machine learning for grouping sketch diagram strokes
Proceedings of the International Symposium on Sketch-Based Interfaces and Modeling
Application of data mining techniques on EMG registers of hemiplegic patients
ICDM'13 Proceedings of the 13th international conference on Advances in Data Mining: applications and theoretical aspects
A hybrid decision tree classifier
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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The alternating decision tree (ADTree) is a successful classification technique that combines decision trees with the predictive accuracy of boosting into a set of interpretable classification rules. The original formulation of the tree induction algorithm restricted attention to binary classification problems. This paper empirically evaluates several wrapper methods for extending the algorithm to the multiclass case by splitting the problem into several two-class problems. Seeking a more natural solution we then adapt the multiclass LogitBoost and AdaBoost.MH procedures to induce alternating decision trees directly. Experimental results confirm that these procedures are comparable with wrapper methods that are based on the original ADTree formulation in accuracy, while inducing much smaller trees.