C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
Error reduction through learning multiple descriptions
Machine Learning
Option Decision Trees with Majority Votes
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
An empirical evaluation of bagging and boosting
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Active learning using adaptive resampling
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Randomizing Outputs to Increase Prediction Accuracy
Machine Learning
Machine Learning
An Adaptive Version of the Boost by Majority Algorithm
Machine Learning
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
Machine Learning
Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sum Versus Vote Fusion in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving nonparametric regression methods by bagging and boosting
Computational Statistics & Data Analysis - Nonlinear methods and data mining
Distributed learning with bagging-like performance
Pattern Recognition Letters
Boosting Applied toe Word Sense Disambiguation
ECML '00 Proceedings of the 11th European Conference on Machine Learning
Analysis of the Performance of AdaBoost.M2 for the Simulated Digit-Recognition-Example
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Class Probability Estimation and Cost-Sensitive Classification Decisions
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Pairwise Classification as an Ensemble Technique
ECML '02 Proceedings of the 13th European Conference on Machine Learning
A Study on the Effect of Cooperative Evolution on Concept Learning
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
Learning First Order Logic Time Series Classifiers: Rules and Boosting
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
The Role of Combining Rules in Bagging and Boosting
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Ensembles of Learning Machines
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
Shared Ensemble Learning Using Multi-trees
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Wrapping Boosters against Noise
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Bagging Can Stabilize without Reducing Variance
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Scaling Up a Boosting-Based Learner via Adaptive Sampling
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Optimizing the Induction of Alternating Decision Trees
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
EuroCOLT '99 Proceedings of the 4th European Conference on Computational Learning Theory
Stacking for Misclassification Cost Performance
AI '01 Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Theoretical Views of Boosting and Applications
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
From Ensemble Methods to Comprehensible Models
DS '02 Proceedings of the 5th International Conference on Discovery Science
Applying Boosting to Similarity Literals for Time Series Classification
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Boosting in Linear Discriminant Analysis
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Input Decimation Ensembles: Decorrelation through Dimensionality Reduction
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Limiting the Number of Trees in Random Forests
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Improving Product by Moderating k-NN Classifiers
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Tuning Cost-Sensitive Boosting and Its Application to Melanoma Diagnosis
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Feature Weighted Ensemble Classifiers - A Modified Decision Scheme
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Highlighting Hard Patterns via AdaBoost Weights Evolution
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Distributed Pasting of Small Votes
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Boosted Tree Ensembles for Solving Multiclass Problems
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Boosting and Classification of Electronic Nose Data
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Boosting of Tree-Based Classifiers for Predictive Risk Modeling in GIS
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Smooth Boosting and Learning with Malicious Noise
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
An Empirical Comparison of Pruning Methods for Ensemble Classifiers
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Algorithmic Aspects of Boosting
Progress in Discovery Science, Final Report of the Japanese Discovery Science Project
Bagging improves uncertainty representation in evidential pattern classification
Technologies for constructing intelligent systems
Efficient handling of high-dimensional feature spaces by randomized classifier ensembles
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Boosting in the presence of noise
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
An introduction to boosting and leveraging
Advanced lectures on machine learning
Online Ensemble Learning: An Empirical Study
Machine Learning
Relational concept learning by cooperative evolution
Journal of Experimental Algorithmics (JEA)
The Journal of Machine Learning Research
On the algorithmic implementation of multiclass kernel-based vector machines
The Journal of Machine Learning Research
Smooth boosting and learning with malicious noise
The Journal of Machine Learning Research
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Comparing Pure Parallel Ensemble Creation Techniques Against Bagging
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Greedy algorithms for classification—consistency, convergence rates, and adaptivity
The Journal of Machine Learning Research
Model selection for medical diagnosis decision support systems
Decision Support Systems
Machine Learning
Learning Ensembles from Bites: A Scalable and Accurate Approach
The Journal of Machine Learning Research
Learning from imbalanced data sets with boosting and data generation: the DataBoost-IM approach
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Multistrategy Ensemble Learning: Reducing Error by Combining Ensemble Learning Techniques
IEEE Transactions on Knowledge and Data Engineering
Comments on "A parallel mixture of SVMs for very large scale problems"
Neural Computation
Learning to detect malicious executables in the wild
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Leveraging the margin more carefully
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Robust feature induction for support vector machines
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods
The Journal of Machine Learning Research
An evaluation of statistical spam filtering techniques
ACM Transactions on Asian Language Information Processing (TALIP)
Neural network ensemble strategies for financial decision applications
Computers and Operations Research
Learning to predict train wheel failures
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Design of a next generation sampling service for large scale data analysis applications
Proceedings of the 19th annual international conference on Supercomputing
Closed-form dual perturb and combine for tree-based models
ICML '05 Proceedings of the 22nd international conference on Machine learning
A smoothed boosting algorithm using probabilistic output codes
ICML '05 Proceedings of the 22nd international conference on Machine learning
Unifying the error-correcting and output-code AdaBoost within the margin framework
ICML '05 Proceedings of the 22nd international conference on Machine learning
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Boosting in the presence of noise
Journal of Computer and System Sciences - Special issue: Learning theory 2003
A cross-comparison of two clustering methods
ELDS '01 Proceedings of the workshop on Evaluation for Language and Dialogue Systems - Volume 9
Different Paradigms for Choosing Sequential Reweighting Algorithms
Neural Computation
Attractor Networks for Shape Recognition
Neural Computation
Neural Computation
Adapting k-means for supervised clustering
Applied Intelligence
Machine Learning
Pruning in ordered bagging ensembles
ICML '06 Proceedings of the 23rd international conference on Machine learning
Improving cooperative GP ensemble with clustering and pruning for pattern classification
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A probabilistic classifier system and its application in data mining
Evolutionary Computation
Demonstrating the stability of support vector machines for classification
Signal Processing - Signal processing in UWB communications
An analysis of diversity measures
Machine Learning
A Comparison of Decision Tree Ensemble Creation Techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel matching pursuit classifier ensemble
Pattern Recognition
Classification by evolutionary ensembles
Pattern Recognition
Using boosting to prune bagging ensembles
Pattern Recognition Letters
Experimental study for the comparison of classifier combination methods
Pattern Recognition
A cooperative constructive method for neural networks for pattern recognition
Pattern Recognition
Parallelizing AdaBoost by weights dynamics
Computational Statistics & Data Analysis
Unifying multi-class AdaBoost algorithms with binary base learners under the margin framework
Pattern Recognition Letters
Rough set Based Ensemble Classifier forWeb Page Classification
Fundamenta Informaticae
Multi-Classifier Systems: Review and a roadmap for developers
International Journal of Hybrid Intelligent Systems
Multi-Class Learning by Smoothed Boosting
Machine Learning
Ensemble Pruning Via Semi-definite Programming
The Journal of Machine Learning Research
Learning to Detect and Classify Malicious Executables in the Wild
The Journal of Machine Learning Research
Nonlinear Boosting Projections for Ensemble Construction
The Journal of Machine Learning Research
Noise Tolerant Variants of the Perceptron Algorithm
The Journal of Machine Learning Research
Anytime Learning of Decision Trees
The Journal of Machine Learning Research
Decision-tree instance-space decomposition with grouped gain-ratio
Information Sciences: an International Journal
Semantic parsing with structured SVM ensemble classification models
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
A comparative study of classification methods for microarray data analysis
AusDM '06 Proceedings of the fifth Australasian conference on Data mining and analystics - Volume 61
A maximally diversified multiple decision tree algorithm for microarray data classification
WISB '06 Proceedings of the 2006 workshop on Intelligent systems for bioinformatics - Volume 73
EROS: Ensemble rough subspaces
Pattern Recognition
Increasing the Robustness of Boosting Algorithms within the Linear-programming Framework
Journal of VLSI Signal Processing Systems
Robust face detection in airports
EURASIP Journal on Applied Signal Processing
An experimental evaluation of ensemble methods for EEG signal classification
Pattern Recognition Letters
Intelligent Data Analysis
Boosting strategy for classification
Intelligent Data Analysis
Boosting interval based literals
Intelligent Data Analysis
Classifier ensembles: Select real-world applications
Information Fusion
A local boosting algorithm for solving classification problems
Computational Statistics & Data Analysis
Machine learning: a review of classification and combining techniques
Artificial Intelligence Review
Improving multiclass pattern recognition with a co-evolutionary RBFNN
Pattern Recognition Letters
An efficient modified boosting method for solving classification problems
Journal of Computational and Applied Mathematics
Boosting recombined weak classifiers
Pattern Recognition Letters
Evolutionary multiobjective optimization for the design of fuzzy rule-based ensemble classifiers
International Journal of Hybrid Intelligent Systems - Hybrid Intelligent systems in Ensembles
A boosting approach to remove class label noise
International Journal of Hybrid Intelligent Systems - Hybrid Intelligent systems in Ensembles
Genetic rule selection with a multi-classifier coding scheme for ensemble classifier design
International Journal of Hybrid Intelligent Systems - Hybridization of Intelligent Systems
An experimental comparative study of web mining methods for recommender systems
DIWED'06 Proceedings of the 6th WSEAS International Conference on Distance Learning and Web Engineering
A semi-random multiple decision-tree algorithm for mining data streams
Journal of Computer Science and Technology
RotBoost: A technique for combining Rotation Forest and AdaBoost
Pattern Recognition Letters
AdaBoost with SVM-based component classifiers
Engineering Applications of Artificial Intelligence
Maximum likelihood rule ensembles
Proceedings of the 25th international conference on Machine learning
Random classification noise defeats all convex potential boosters
Proceedings of the 25th international conference on Machine learning
Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts
The Journal of Machine Learning Research
Support Vector Machinery for Infinite Ensemble Learning
The Journal of Machine Learning Research
Boosting: a classification method for remote sensing
International Journal of Remote Sensing
Class-switching neural network ensembles
Neurocomputing
The combination of multiple classifiers using an evidential reasoning approach
Artificial Intelligence
Investigating methods for improving bagged k-NN classifiers
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
Distributed mining of censored production rules in data streams: an evolutionary approach
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
Boosted Bayesian network classifiers
Machine Learning
Influence of Resampling and Weighting on Diversity and Accuracy of Classifier Ensembles
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Avoiding Boosting Overfitting by Removing Confusing Samples
ECML '07 Proceedings of the 18th European conference on Machine Learning
CTC: An Alternative to Extract Explanation from Bagging
Current Topics in Artificial Intelligence
Neural Network Ensembles for Classification Problems Using Multiobjective Genetic Algorithms
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
How an Ensemble Method Can Compute a Comprehensible Model
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Consistency of Random Forests and Other Averaging Classifiers
The Journal of Machine Learning Research
Ensemble of support vector machines for land cover classification
International Journal of Remote Sensing
Boosting random subspace method
Neural Networks
Boosting and measuring the performance of ensembles for a successful database marketing
Expert Systems with Applications: An International Journal
Standard errors for bagged and random forest estimators
Computational Statistics & Data Analysis
Diversity of ability and cognitive style for group decision processes
Information Sciences: an International Journal
Using Boosting to prune Double-Bagging ensembles
Computational Statistics & Data Analysis
Classification algorithm sensitivity to training data with non representative attribute noise
Decision Support Systems
Fuzzy ensemble clustering based on random projections for DNA microarray data analysis
Artificial Intelligence in Medicine
Boosting One-Class Support Vector Machines for Multi-Class Classification
Applied Artificial Intelligence
Boosting k-nearest neighbor classifier by means of input space projection
Expert Systems with Applications: An International Journal
Negative correlation in incremental learning
Natural Computing: an international journal
Supervised projection approach for boosting classifiers
Pattern Recognition
A novel method for constructing ensemble classifiers
Statistics and Computing
Selective Ensemble Algorithms of Support Vector Machines Based on Constraint Projection
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Supervised Machine Learning: A Review of Classification Techniques
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
MTForest: Ensemble Decision Trees based on Multi-Task Learning
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Structure identification of Bayesian classifiers based on GMDH
Knowledge-Based Systems
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A Bayesian Random Split to Build Ensembles of Classification Trees
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
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
Comparison of Bagging and Boosting Algorithms on Sample and Feature Weighting
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Out-of-bag estimation of the optimal sample size in bagging
Pattern Recognition
ODDboost: Incorporating Posterior Estimates into AdaBoost
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Is bagging effective in the classification of small-sample genomic and proteomic data?
EURASIP Journal on Bioinformatics and Systems Biology - Special issue on applications of signal procesing techniques to bioinformatics, genomics, and proteomics
Computational Statistics & Data Analysis
Spectrum of variable-random trees
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
A new technique for combining multiple classifiers using the dempster-shafer theory of evidence
Journal of Artificial Intelligence Research
A brief introduction to boosting
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
A data driven ensemble classifier for credit scoring analysis
Expert Systems with Applications: An International Journal
Boosting face identification in airports
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Learning with labeled sessions
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
A general magnitude-preserving boosting algorithm for search ranking
Proceedings of the 18th ACM conference on Information and knowledge management
Constructing ensembles of classifiers by means of weighted instance selection
IEEE Transactions on Neural Networks
Multiple classifier application to credit risk assessment
Expert Systems with Applications: An International Journal
A hybrid approach for efficient ensembles
Decision Support Systems
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
The diversity/accuracy dilemma: an empirical analysis in the context of heterogeneous ensembles
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Evolutionary Ensemble for In Silico Prediction of Ames Test Mutagenicity
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
A classifier ensemble based on performance level estimation
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Feature selection in heterogeneous structure of ensembles: a genetic algorithm approach
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Ensembles of neural networks with generalization capabilities for vehicle fault diagnostics
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Optimal ensemble construction via meta-evolutionary ensembles
Expert Systems with Applications: An International Journal
Group search optimizer: an optimization algorithm inspired by animal searching behavior
IEEE Transactions on Evolutionary Computation
A novel dynamic fusion method using localized generalization error model
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Switching class labels to generate classification ensembles
Pattern Recognition
The Naive Bayes Mystery: A classification detective story
Pattern Recognition Letters
Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination
The Journal of Machine Learning Research
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
Contextual classifier ensembles
BIS'07 Proceedings of the 10th international conference on Business information systems
Averaged boosting: a noise-robust ensemble method
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
Improving performance of decision tree algorithms with multi-edited nearest neighbor rule
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
An improved random subspace method and its application to EEG signal classification
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Ensemble learning methods for classifying EEG signals
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Cooperative coevolutionary ensemble learning
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Evolutionary multiobjective optimization for generating an ensemble of fuzzy rule-based classifiers
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Ensemble techniques for parallel genetic programming based classifiers
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Mining distributed evolving data streams using fractal GP ensembles
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Boosting with averaged weight vectors
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Beam search extraction and forgetting strategies on shared ensembles
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
A new ensemble diversity measure applied to thinning ensembles
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Ensemble methods for noise elimination in classification problems
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Classification of aircraft maneuvers for fault detection
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
An approach for selective ensemble feature selection based on rough set theory
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
A survey on the application of genetic programming to classification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
The impact of random samples in ensemble classifiers
Proceedings of the 2010 ACM Symposium on Applied Computing
On selection and combination of weak learners in AdaBoost
Pattern Recognition Letters
PRIB'07 Proceedings of the 2nd IAPR international conference on Pattern recognition in bioinformatics
Selective ensemble of decision trees
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Local decision bagging of binary neural classifiers
Canadian AI'08 Proceedings of the Canadian Society for computational studies of intelligence, 21st conference on Advances in artificial intelligence
Experimental evaluation of diversity measures of combined classifiers
AIKED'10 Proceedings of the 9th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
When to choose an ensemble classifier model for data mining
International Journal of Business Intelligence and Data Mining
ENDER: a statistical framework for boosting decision rules
Data Mining and Knowledge Discovery
A dynamic classifier ensemble selection approach for noise data
Information Sciences: an International Journal
Ensemble pruning via individual contribution ordering
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
International Journal of Approximate Reasoning
Ensemble missing data techniques for software effort prediction
Intelligent Data Analysis
Vertical bagging decision trees model for credit scoring
Expert Systems with Applications: An International Journal
Comparing combiner systems using diversity measures
SIP'10 Proceedings of the 9th WSEAS international conference on Signal processing
Meta-learning in grid-based data mining systems
International Journal of Communication Networks and Distributed Systems
Variable selection using random forests
Pattern Recognition Letters
Expert Systems with Applications: An International Journal
Medical case retrieval from a committee of decision trees
IEEE Transactions on Information Technology in Biomedicine
Mining data with random forests: A survey and results of new tests
Pattern Recognition
Edited AdaBoost by weighted kNN
Neurocomputing
A comparison of three voting methods for bagging with the MLEM2 algorithm
IDEAL'10 Proceedings of the 11th international conference on Intelligent data engineering and automated learning
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Learning with ensembles of randomized trees: new insights
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Parallel Approach for Ensemble Learning with Locally Coupled Neural Networks
Neural Processing Letters
An efficient classifier design integrating rough set and set oriented database operations
Applied Soft Computing
Implementation of a scalable decision forest model based on information theory
Expert Systems with Applications: An International Journal
Classifier fusion in the Dempster--Shafer framework using optimized t-norm based combination rules
International Journal of Approximate Reasoning
Inference on the prediction of ensembles of infinite size
Pattern Recognition
Tree Decomposition for Large-Scale SVM Problems
The Journal of Machine Learning Research
Learning random forests for ranking
Frontiers of Computer Science in China
S-adaboost and pattern detection in complex environment
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Combining bagging, boosting, rotation forest and random subspace methods
Artificial Intelligence Review
BSPNN: boosted subspace probabilistic neural network for email security
Artificial Intelligence Review
Cooperative evolutive concept learning: an empirical study
EC'05 Proceedings of the 6th WSEAS international conference on Evolutionary computing
A comparison of soft fusion methods under different bagging scenarios
CIMMACS'07 Proceedings of the 6th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics
Partial AUC maximization in a linear combination of dichotomizers
Pattern Recognition
Improving the accuracy of suicide attempter classification
Artificial Intelligence in Medicine
Case-based reasoning support for liver disease diagnosis
Artificial Intelligence in Medicine
Random ensemble decision trees for learning concept-drifting data streams
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin
The Journal of Machine Learning Research
Fusion of similarity measures for time series classification
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
Interactive object recognition using proprioceptive and auditory feedback
International Journal of Robotics Research
Clustering students to generate an ensemble to improve standard test score predictions
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
GRASP forest: a new ensemble method for trees
MCS'11 Proceedings of the 10th international conference on Multiple classifier systems
Random feature weights for decision tree ensemble construction
Information Fusion
An XML-based representational document format for FRBR
WISS'10 Proceedings of the 2010 international conference on Web information systems engineering
Dynamic classifier ensemble model for customer classification with imbalanced class distribution
Expert Systems with Applications: An International Journal
Self-adaptation of parameters in a learning classifier system ensemble machine
International Journal of Applied Mathematics and Computer Science - Computational Intelligence in Modern Control Systems
Improvements in image categorization using codebook ensembles
Image and Vision Computing
Decision forests with oblique decision trees
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
When efficient model averaging out-performs boosting and bagging
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Combined gene selection methods for microarray data analysis
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Variable randomness in decision tree ensembles
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Improving on bagging with input smearing
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Many are better than one: improving probabilistic estimates from decision trees
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
Ensembles of balanced nested dichotomies for multi-class problems
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Two credit scoring models based on dual strategy ensemble trees
Knowledge-Based Systems
A hybrid ensemble approach for enterprise credit risk assessment based on Support Vector Machine
Expert Systems with Applications: An International Journal
Ensemble learning for keyphrases extraction from scientific document
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Combining multiple clusterings via k-modes algorithm
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Hellinger distance decision trees are robust and skew-insensitive
Data Mining and Knowledge Discovery
Building ensembles of neural networks with class-switching
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Constructing rough decision forests
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Ensemble learning with supervised kernels
ECML'05 Proceedings of the 16th European conference on Machine Learning
ECML'05 Proceedings of the 16th European conference on Machine Learning
Using decision tree models and diversity measures in the selection of ensemble classification models
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Design of multiple classifier systems for time series data
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Dynamics of variance reduction in bagging and other techniques based on randomisation
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Analysis and modelling of diversity contribution to ensemble-based texture recognition performance
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Maximizing tree diversity by building complete-random decision trees
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Boosting parallel perceptrons for label noise reduction in classification problems
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Learning the bias of a classifier in a GA-Based inductive learning environment
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Using boolean differences for discovering ill-defined attributes in propositional machine learning
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Generating diverse ensembles to counter the problem of class imbalance
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Ensemble algorithms for feature selection
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Bagging schemes on the presence of class noise in classification
Expert Systems with Applications: An International Journal
User preferences based software defect detection algorithms selection using MCDM
Information Sciences: an International Journal
Modelling metabolic pathways using stochastic logic programs-based ensemble methods
CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology
Supervised subspace projections for constructing ensembles of classifiers
Information Sciences: an International Journal
Segmented document classification: problem and solution
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
Coupling adaboost and random subspace for diversified fisher linear discriminant
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
A group search optimizer for neural network training
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
Bagging decision trees on data sets with classification noise
FoIKS'10 Proceedings of the 6th international conference on Foundations of Information and Knowledge Systems
A double pruning algorithm for classification ensembles
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Multi-information ensemble diversity
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Handling different categories of concept drifts in data streams using distributed GP
EuroGP'10 Proceedings of the 13th European conference on Genetic Programming
Pruning adaptive boosting ensembles by means of a genetic algorithm
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Ensemble based sensing anomaly detection in wireless sensor networks
Expert Systems with Applications: An International Journal
Identifying feature relevance using a random forest
SLSFS'05 Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection
Ensembles of bireducts: towards robust classification and simple representation
FGIT'11 Proceedings of the Third international conference on Future Generation Information Technology
Beyond trees: adopting MITI to learn rules and ensemble classifiers for multi-instance data
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
An empirical evaluation of bagging with different algorithms on imbalanced data
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
A new ensemble method for gold mining problems: Predicting technology transfer
Electronic Commerce Research and Applications
PISA: A framework for multiagent classification using argumentation
Data & Knowledge Engineering
A graph mining approach for detecting unknown malwares
Journal of Visual Languages and Computing
Integration of intelligent information technologies ensembles for modeling and classification
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Pattern Recognition Letters
An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration
ACM Transactions on Intelligent Systems and Technology (TIST)
Multi-agent based classification using argumentation from experience
Autonomous Agents and Multi-Agent Systems
A noise-detection based AdaBoost algorithm for mislabeled data
Pattern Recognition
Analysis of a random forests model
The Journal of Machine Learning Research
Dynamic fusion method using Localized Generalization Error Model
Information Sciences: an International Journal
An interactive approach to semantic modeling of indoor scenes with an RGBD camera
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Rough set Based Ensemble Classifier forWeb Page Classification
Fundamenta Informaticae
A heuristically perturbation of dataset to achieve a diverse ensemble of classifiers
MCPR'12 Proceedings of the 4th Mexican conference on Pattern Recognition
Review: Supervised classification and mathematical optimization
Computers and Operations Research
Design of a Fuzzy-based Decision Support System for Coronary Heart Disease Diagnosis
Journal of Medical Systems
Multi-domain learning: when do domains matter?
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
New machine learning algorithm: random forest
ICICA'12 Proceedings of the Third international conference on Information Computing and Applications
Diversity regularized ensemble pruning
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Artificial neural network training using a new efficient optimization algorithm
Applied Soft Computing
How large should ensembles of classifiers be?
Pattern Recognition
A learning framework for the optimization and automation of document binarization methods
Computer Vision and Image Understanding
The use of artificial-intelligence-based ensembles for intrusion detection: a review
Applied Computational Intelligence and Soft Computing
Bagging and Boosting statistical machine translation systems
Artificial Intelligence
A Novel Emotion Recognition Method Based on Ensemble Learning and Rough Set Theory
International Journal of Cognitive Informatics and Natural Intelligence
Classifying Very High-Dimensional Data with Random Forests Built from Small Subspaces
International Journal of Data Warehousing and Mining
Information Sciences: an International Journal
Reducing overfitting of AdaBoost by clustering-based pruning of hard examples
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
Classification of brain-computer interface data
AusDM '08 Proceedings of the 7th Australasian Data Mining Conference - Volume 87
Decision trees: a recent overview
Artificial Intelligence Review
Sentiment polarity detection in Spanish reviews combining supervised and unsupervised approaches
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Learning regression ensembles with genetic programming at scale
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Inter-training: Exploiting unlabeled data in multi-classifier systems
Knowledge-Based Systems
HDM-Analyser: a hybrid analysis approach based on data mining techniques for malware detection
Journal in Computer Virology
Embedding change rate estimation based on ensemble learning
Proceedings of the first ACM workshop on Information hiding and multimedia security
Empirical study of bagging predictors on medical data
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
Ad click prediction: a view from the trenches
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
On the effect of calibration in classifier combination
Applied Intelligence
Classification of Alzheimer Diagnosis from ADNI Plasma Biomarker Data
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
Information Sciences: an International Journal
Improving Text Classification Accuracy by Training Label Cleaning
ACM Transactions on Information Systems (TOIS)
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
On the doubt about margin explanation of boosting
Artificial Intelligence
The C-loss function for pattern classification
Pattern Recognition
An investigation into the application of ensemble learning for entailment classification
Information Processing and Management: an International Journal
GA-Ensemble: a genetic algorithm for robust ensembles
Computational Statistics
Comparing ensemble learning methods based on decision tree classifiers for protein fold recognition
International Journal of Data Mining and Bioinformatics
Machine learning-based classifiers ensemble for credit risk assessment
International Journal of Electronic Finance
A boosted SVM based ensemble classifier for sentiment analysis of online reviews
ACM SIGAPP Applied Computing Review
Expert Systems with Applications: An International Journal
A metric for unsupervised metalearning
Intelligent Data Analysis
Hi-index | 0.02 |
Bagging and boosting are methods that generate a diverse ensemble of classifiers by manipulating the training data given to a “base” learning algorithm. Breiman has pointed out that they rely for their effectiveness on the instability of the base learning algorithm. An alternative approach to generating an ensemble is to randomize the internal decisions made by the base algorithm. This general approach has been studied previously by Ali and Pazzani and by Dietterich and Kong. This paper compares the effectiveness of randomization, bagging, and boosting for improving the performance of the decision-tree algorithm C4.5. The experiments show that in situations with little or no classification noise, randomization is competitive with (and perhaps slightly superior to) bagging but not as accurate as boosting. In situations with substantial classification noise, bagging is much better than boosting, and sometimes better than randomization.