Rotation Forest: A New Classifier Ensemble Method
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- Type
- article
- Published
- 2006-10-01
- Cited by
- 1,975
- References
- 47
- OpenAlex
- https://openalex.org/W2150757437
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:6847493
Keywords
Random forest, AdaBoost, Computer science, Classifier (UML), Artificial intelligence
References
- Special Invited Paper-Additive logistic regression: A statistical view of boosting
- Data Mining - Concepts and Techniques
- Programs for Machine Learning
- Multiple Classifier Systems
- Pruning Adaptive Boosting
- Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers
- Improved Generalization Through Explicit Optimization of Margins
- Boosting and Microarray Data
- A Data Complexity Analysis of Comparative Advantages of Decision Forest Constructors
- An Optimal Set of Discriminant Vectors
- Boosting the margin: A new explanation for the effectiveness of voting methods
- A decision-theoretic generalization of on-line learning and an application to boosting
- Input decimated ensembles
- Application of the Karhunen-Loève Expansion to Feature Selection and Ordering
- Improved Boosting Algorithms Using Confidence-rated Predictions
- Diversity in multiple classifier systems
- A new approach to feature selection based on the Karhunen-Loeve expansion
- Arcing classifier (with discussion and a rejoinder by the author)
- UCI Repository of machine learning databases
- MultiBoosting: A Technique for Combining Boosting and Wagging
Cited by
- Dynamic classifier ensemble using classification confidence
- Sequence-based prediction of protein-protein interactions by means of rotation forest and autocorrelation descriptor.
- Global and Local (Glocal) Bagging Approach for Classifying Noisy Dataset
- Vineyard water status assessment using on-the-go thermal imaging and machine learning
- The CCB-ID approach to tree species mapping with airborne imaging spectroscopy
- Embedding Undersampling Rotation Forest for Imbalanced Problem
- Tweet Collect: short text message collection using automatic query expansion and classification
- Mal-ID: Automatic Malware Detection Using Common Segment Analysis and Meta-Features
- 3-level Confidence Voting Strategy for Dynamic Fusion-Selection of Classifier Ensembles
- Rotation of random forests for genomic and proteomic classification problems.
- Machine learning analysis of the cultural and cross-cultural aspects of beauty in music
- System of Boosting Voting with Multiple Learning Algorithms
- Predictive analysis of coronary plaque morphology and composition on a one year timescale
- A Deep Neural Network Approach to Automatic Birdsong Recognition
- Discriminant Random Forests
- Modifications of the construction and voting mechanisms of the Random Forests Algorithm
- A Comparative Study of MRI Data using Various Machine Learning and Pattern Recognition Algorithms to Detect Brain Abnormalities
- Extracting group relationships within changing software using text analysis
- Argumentation Based Joint Learning: A Novel Ensemble Learning Approach
- Diversity, margins and non-stationary learning
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