C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
The Random Subspace Method for Constructing Decision Forests
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Improved Generalization Through Explicit Optimization of Margins
Machine Learning
MultiBoosting: A Technique for Combining Boosting and Wagging
Machine Learning
Data mining: concepts and techniques
Data mining: concepts and techniques
Machine Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Machine Learning
Inference for the Generalization Error
Machine Learning
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
An Optimal Set of Discriminant Vectors
IEEE Transactions on Computers
Application of the Karhunen-Loève Expansion to Feature Selection and Ordering
IEEE Transactions on Computers
Boosting with averaged weight vectors
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Combining feature subsets in feature selection
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Nonlinear Boosting Projections for Ensemble Construction
The Journal of Machine Learning Research
Classifier Ensembles with a Random Linear Oracle
IEEE Transactions on Knowledge and Data Engineering
An efficient modified boosting method for solving classification problems
Journal of Computational and Applied Mathematics
Classifier ensemble selection using hybrid genetic algorithms
Pattern Recognition Letters
Boosting recombined weak classifiers
Pattern Recognition Letters
Cancer classification using Rotation Forest
Computers in Biology and Medicine
RotBoost: A technique for combining Rotation Forest and AdaBoost
Pattern Recognition Letters
Increasing classification efficiency with multiple mirror classifiers
Expert Systems with Applications: An International Journal
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Forest-RK: A New Random Forest Induction Method
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
A Boost Voting Strategy for Knowledge Integration and Decision Making
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Feature Selection and Classification for Small Gene Sets
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Using Boosting to prune Double-Bagging ensembles
Computational Statistics & Data Analysis
Ensemble of multiple Palmprint representation
Expert Systems with Applications: An International Journal
Data dependency in multiple classifier systems
Pattern Recognition
Input Decimated Ensemble based on Neighborhood Preserving Embedding for spectrogram classification
Expert Systems with Applications: An International Journal
Semi-random subspace method for face recognition
Image and Vision Computing
A novel method for constructing ensemble classifiers
Statistics and Computing
On the Effectiveness of Diversity When Training Multiple Classifier Systems
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A Study of Random Linear Oracle Ensembles
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Constraint projections for ensemble learning
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Rotation-based model trees for classification
International Journal of Data Analysis Techniques and Strategies
Indexing ICD-9 codes for free-textual clinical diagnosis records by a new ensemble classifier
International Journal of Computational Intelligence in Bioinformatics and Systems Biology
Statistical Instance-Based Ensemble Pruning for Multi-class Problems
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Randomized Probabilistic Latent Semantic Analysis for Scene Recognition
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
DensityRank: a novel feature ranking method based on kernel estimation
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
On the selection of decision trees in random forests
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Online evolutionary context-aware classifier ensemble framework for object recognition
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Bagging Constraint Score for feature selection with pairwise constraints
Pattern Recognition
Ensemble classification based on generalized additive models
Computational Statistics & Data Analysis
An experimental study on rotation forest ensembles
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Creating ensembles of classifiers via fuzzy clustering and deflection
Fuzzy Sets and Systems
Towards a better understanding of random forests through the study of strength and correlation
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Selecting features from multiple feature sets for SVM committee-based screening of human larynx
Expert Systems with Applications: An International Journal
International Journal of Knowledge Engineering and Data Mining
Mining data with random forests: A survey and results of new tests
Pattern Recognition
Reduced Reward-punishment editing for building ensembles of classifiers
Expert Systems with Applications: An International Journal
A comparative study on the performance of several ensemble methods with low subsampling ratio
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Active learning from stream data using optimal weight classifier ensemble
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Greedy optimization classifiers ensemble based on diversity
Pattern Recognition
Ensembles of probability estimation trees for customer churn prediction
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Random projections for SVM ensembles
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Rotation forest on microarray domain: PCA versus ICA
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Inference on the prediction of ensembles of infinite size
Pattern Recognition
Filtering microblogging messages for social tv
Proceedings of the 20th international conference companion on World wide web
Combining bagging, boosting, rotation forest and random subspace methods
Artificial Intelligence Review
Municipal revenue prediction by ensembles of neural networks and support vector machines
WSEAS Transactions on Computers
Municipal revenue prediction by support vector machine ensembles
ICCOMP'10 Proceedings of the 14th WSEAS international conference on Computers: part of the 14th WSEAS CSCC multiconference - Volume I
An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction
Expert Systems with Applications: An International Journal
Estimation of optimal sample size of decision forest with SVM using embedded cross-validation method
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
Random projections for linear SVM ensembles
Applied Intelligence
Rotation forest with GEP-induced expression trees
KES-AMSTA'11 Proceedings of the 5th KES international conference on Agent and multi-agent systems: technologies and applications
Using ensembles of regression trees to monitor lubricating oil quality
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part I
Multi-modal biometric emotion recognition using classifier ensembles
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part I
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Ensemble pruning via base-classifier replacement
WAIM'11 Proceedings of the 12th international conference on Web-age information management
Ensembles of decision trees for imbalanced data
MCS'11 Proceedings of the 10th international conference on Multiple classifier systems
Investigation of random subspace and random forest methods applied to property valuation data
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part I
Clustering and classification techniques for blind predictions of reservoir facies
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
Semi-supervised classification based on random subspace dimensionality reduction
Pattern Recognition
Computer Methods and Programs in Biomedicine
Making Diversity Enhancement Based on Multiple Classifier System by Weight Tuning
Neural Processing Letters
On selecting additional predictive models in double bagging type ensemble method
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part IV
Using rotation forest for protein fold prediction problem: an empirical study
EvoBIO'10 Proceedings of the 8th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Novel ensemble methods for regression via classification problems
Expert Systems with Applications: An International Journal
Supervised subspace projections for constructing ensembles of classifiers
Information Sciences: an International Journal
Semi-supervised ensemble classification in subspaces
Applied Soft Computing
An experimental study on ensembles of functional trees
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Unsupervised and supervised learning in cascade for petroleum geology
Expert Systems with Applications: An International Journal
Exploring the behaviour of base classifiers in credit scoring ensembles
Expert Systems with Applications: An International Journal
CCC: classifier combination via classifier
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
Improving bagging performance through multi-algorithm ensembles
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
From cluster ensemble to structure ensemble
Information Sciences: an International Journal
Diagnosing Breast Masses in Digital Mammography Using Feature Selection and Ensemble Methods
Journal of Medical Systems
An associative memory approach to medical decision support systems
Computer Methods and Programs in Biomedicine
Two-level classifier ensembles for credit risk assessment
Expert Systems with Applications: An International Journal
DRFLogitBoost: a double randomized decision forest incorporated with logitboosted decision stumps
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
ReinSel: A class-based mechanism for feature selection in ensemble of classifiers
Applied Soft Computing
Ensemble pruning using harmony search
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Classification of Epilepsy Using High-Order Spectra Features and Principle Component Analysis
Journal of Medical Systems
Pattern Recognition Letters
Network intrusion detection system: a machine learning approach
Intelligent Decision Technologies
Investigation of rotation forest method applied to property price prediction
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Mal-ID: automatic malware detection using common segment analysis and meta-features
The Journal of Machine Learning Research
Wind turbines fault diagnosis using ensemble classifiers
ICDM'12 Proceedings of the 12th Industrial conference on Advances in Data Mining: applications and theoretical aspects
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
Ensemble approaches for regression: A survey
ACM Computing Surveys (CSUR)
Accurate Prediction of Coronary Artery Disease Using Reliable Diagnosis System
Journal of Medical Systems
Effective Diagnosis of Coronary Artery Disease Using The Rotation Forest Ensemble Method
Journal of Medical Systems
Multi-label ensemble based on variable pairwise constraint projection
Information Sciences: an International Journal
How large should ensembles of classifiers be?
Pattern Recognition
Decision trees: a recent overview
Artificial Intelligence Review
Evaluating data mining algorithms using molecular dynamics trajectories
International Journal of Data Mining and Bioinformatics
Malware detection by pruning of parallel ensembles using harmony search
Pattern Recognition Letters
A remote sensing image classification method based on extreme learning machine ensemble
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
Early detection of outgoing spammers in large-scale service provider networks
DIMVA'13 Proceedings of the 10th international conference on Detection of Intrusions and Malware, and Vulnerability Assessment
Classifier Ensemble Methods for Diagnosing COPD from Volatile Organic Compounds in Exhaled Air
International Journal of Knowledge Discovery in Bioinformatics
Editorial: Modifications of the construction and voting mechanisms of the Random Forests Algorithm
Data & Knowledge Engineering
An investigation into the application of ensemble learning for entailment classification
Information Processing and Management: an International Journal
Learning ensemble classifiers via restricted Boltzmann machines
Pattern Recognition Letters
An improved boosting based on feature selection for corporate bankruptcy prediction
Expert Systems with Applications: An International Journal
Comparing ensemble learning methods based on decision tree classifiers for protein fold recognition
International Journal of Data Mining and Bioinformatics
A boosted SVM based ensemble classifier for sentiment analysis of online reviews
ACM SIGAPP Applied Computing Review
Advanced Engineering Informatics
Artificial Intelligence Review
Prediction of faults-slip-through in large software projects: an empirical evaluation
Software Quality Control
Hybrid extreme rotation forest
Neural Networks
Applications of Hybrid Extreme Rotation Forests for image segmentation
International Journal of Hybrid Intelligent Systems
Hybrid random subsample classifier ensemble for high dimensional data sets
International Journal of Hybrid Intelligent Systems
Integrating global and local application of random subspace ensemble
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Classification of time series by shapelet transformation
Data Mining and Knowledge Discovery
Hi-index | 0.17 |
We propose a method for generating classifier ensembles based on feature extraction. To create the training data for a base classifier, the feature set is randomly split into K subsets (K is a parameter of the algorithm) and Principal Component Analysis (PCA) is applied to each subset. All principal components are retained in order to preserve the variability information in the data. Thus, K axis rotations take place to form the new features for a base classifier. The idea of the rotation approach is to encourage simultaneously individual accuracy and diversity within the ensemble. Diversity is promoted through the feature extraction for each base classifier. Decision trees were chosen here because they are sensitive to rotation of the feature axes, hence the name "forest.” Accuracy is sought by keeping all principal components and also using the whole data set to train each base classifier. Using WEKA, we examined the Rotation Forest ensemble on a random selection of 33 benchmark data sets from the UCI repository and compared it with Bagging, AdaBoost, and Random Forest. The results were favorable to Rotation Forest and prompted an investigation into diversity-accuracy landscape of the ensemble models. Diversity-error diagrams revealed that Rotation Forest ensembles construct individual classifiers which are more accurate than these in AdaBoost and Random Forest, and more diverse than these in Bagging, sometimes more accurate as well.