The Strength of Weak Learnability
Machine Learning
Boosting a weak learning algorithm by majority
COLT '90 Proceedings of the third annual workshop on Computational learning theory
Neural networks and the bias/variance dilemma
Neural Computation
Original Contribution: Stacked generalization
Neural Networks
C4.5: programs for machine learning
C4.5: programs for machine learning
Comparing connectionist and symbolic learning methods
Proceedings of a workshop on Computational learning theory and natural learning systems (vol. 1) : constraints and prospects: constraints and prospects
Boosting a weak learning algorithm by majority
Information and Computation
Machine Learning
Scaling to domains with irrelevant features
Computational learning theory and natural learning systems: Volume IV
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality
Data Mining and Knowledge Discovery
Boosting the margin: A new explanation for the effectiveness of voting methods
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
The Effects of Training Set Size on Decision Tree Complexity
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
UAI '88 Proceedings of the Fourth Annual Conference on Uncertainty in Artificial Intelligence
Option Decision Trees with Majority Votes
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Induction of One-Level Decision Trees
ML '92 Proceedings of the Ninth International Workshop on Machine Learning
Wrappers for Performance Enhancements and Oblivious Decision Graphs.
Wrappers for Performance Enhancements and Oblivious Decision Graphs.
Learning probabilistic relational concept descriptions
Learning probabilistic relational concept descriptions
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Boosting in the limit: maximizing the margin of learned ensembles
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Multiclass learning, boosting, and error-correcting codes
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Feature selection for ensembles
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Class prediction and discovery using gene expression data
RECOMB '00 Proceedings of the fourth annual international conference on Computational molecular biology
Prediction games and arcing algorithms
Neural Computation
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
MultiBoosting: A Technique for Combining Boosting and Wagging
Machine Learning
Using a Neural Network to Approximate an Ensemble of Classifiers
Neural Processing Letters
Machine Learning
Example-Based Object Detection in Images by Components
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning and making decisions when costs and probabilities are both unknown
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Solving regression problems with rule-based ensemble classifiers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
A streaming ensemble algorithm (SEA) for large-scale classification
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Remembrance of circuits past: macromodeling by data mining in large analog design spaces
Proceedings of the 39th annual Design Automation Conference
Machine Learning
Ensembling neural networks: many could be better than all
Artificial Intelligence
Boosting to correct inductive bias in text classification
Proceedings of the eleventh international conference on Information and knowledge management
Adaptive Sampling Methods for Scaling Up Knowledge Discovery Algorithms
Data Mining and Knowledge Discovery
Linear Programming Boosting via Column Generation
Machine Learning
Boosting Methods for Regression
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
A geometric approach to leveraging weak learners
Theoretical Computer Science
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
An Empirical Study of MetaCost Using Boosting Algorithms
ECML '00 Proceedings of the 11th European Conference on Machine Learning
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
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Dynamic Integration of Decision Committees
HiPC '00 Proceedings of the 7th International Conference on High Performance Computing
Induction of Decision Multi-trees Using Levin Search
ICCS '02 Proceedings of the International Conference on Computational Science-Part I
Rule-Based Ensemble Solutions for Regression
MLDM '01 Proceedings of the Second International Workshop on Machine Learning and Data Mining in Pattern Recognition
A New Bootstrapping Method to Improve Classification Performance in Learning Classifier Systems
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Decision-Rule Solutions for Data Mining with Missing Values
IBERAMIA-SBIA '00 Proceedings of the International Joint Conference, 7th Ibero-American Conference on AI: Advances in Artificial Intelligence
Some Enhencements of Decision Tree Bagging
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Bagging and Boosting with Dynamic Integration of Classifiers
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
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 Need for Low Bias Algorithms in Classification Learning from Large Data Sets
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Ensembles of Learning Machines
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
Solving Regression Problems Using Competitive Ensemble Models
AI '02 Proceedings of the 15th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Ensemble Feature Selection Based on Contextual Merit and Correlation Heuristics
ADBIS '01 Proceedings of the 5th East European Conference on Advances in Databases and Information Systems
Boosting Naive Bayes for Claim Fraud Diagnosis
DaWaK 2000 Proceedings of the 4th International Conference on Data Warehousing and Knowledge Discovery
Feature Selection for Ensembles of Simple Bayesian Classifiers
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Is a Greedy Covering Strategy an Extreme Boosting?
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Probing Knowledge in Distributed Data Mining
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Improving the Performance of Boosting for Naive Bayesian Classification
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
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
N-Version Genetic Programming via Fault Masking
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
EuroCOLT '99 Proceedings of the 4th European Conference on Computational Learning Theory
A Combination Scheme for Fuzzy Clustering
AFSS '02 Proceedings of the 2002 AFSS International Conference on Fuzzy Systems. Calcutta: Advances in Soft Computing
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
Weighted Majority Decision among Several Region Rules for Scientific Discovery
DS '99 Proceedings of the Second International Conference on Discovery Science
An Evaluation of Grading Classifiers
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Applying Boosting to Similarity Literals for Time Series Classification
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
Learning Classification RBF Networks by Boosting
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Relationship of Sum and Vote Fusion Strategies
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
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
Using Diversity with Three Variants of Boosting: Aggressive, Conservative, and Inverse
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Boosting as a Monte Carlo Algorithm
AI*IA 01 Proceedings of the 7th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
CAIP '01 Proceedings of the 9th International Conference on Computer Analysis of Images and Patterns
An Empirical Comparison of Pruning Methods for Ensemble Classifiers
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Boosting Density Function Estimators
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Decision Committee Learning with Dynamic Integration of Classifiers
ADBIS-DASFAA '00 Proceedings of the East-European Conference on Advances in Databases and Information Systems Held Jointly with International Conference on Database Systems for Advanced Applications: Current Issues in Databases and Information Systems
Computing Optimal Hypotheses Efficiently for Boosting
Progress in Discovery Science, Final Report of the Japanese Discovery Science Project
Exploiting unlabeled data in ensemble methods
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Minimum majority classification and boosting
Eighteenth national conference on Artificial intelligence
Data mining tasks and methods: Classification: decision-tree discovery
Handbook of data mining and knowledge discovery
Case studies: Public domain, multiple mining tasks systems: MLC++
Handbook of data mining and knowledge discovery
Tree Induction for Probability-Based Ranking
Machine Learning
An introduction to boosting and leveraging
Advanced lectures on machine learning
Behavioral Diversity and a Probabilistically Optimal GP Ensemble
Genetic Programming and Evolvable Machines
Feature selection in data mining
Data mining
Online Ensemble Learning: An Empirical Study
Machine Learning
The Journal of Machine Learning Research
Tree induction vs. logistic regression: a learning-curve analysis
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
Mining concept-drifting data streams using ensemble classifiers
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Active Sampling for Class Probability Estimation and Ranking
Machine Learning
A Case Study of Applying Boosting Naive Bayes to Claim Fraud Diagnosis
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
Design and application of hybrid intelligent systems
Learning Ensembles from Bites: A Scalable and Accurate Approach
The Journal of Machine Learning Research
A study of the behavior of several methods for balancing machine learning training data
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
Genetic programming in classifying large-scale data: an ensemble method
Information Sciences: an International Journal - Special issue: Soft computing data mining
Learning to detect malicious executables in the wild
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A DEA approach for model combination
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods
The Journal of Machine Learning Research
On combining multiple clusterings
Proceedings of the thirteenth ACM international conference on Information and knowledge management
MOB-ESP and other improvements in probability estimation
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Selecting salient features for classification based on neural network committees
Pattern Recognition Letters
Evolutionary approaches to fuzzy modelling for classification
The Knowledge Engineering Review
Robust boosting and its relation to bagging
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Failure detection and localization in component based systems by online tracking
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Automatic identification of music performers with learning ensembles
Artificial Intelligence
Theoretical Bounds of Majority Voting Performance for a Binary Classification Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical voting classification scheme for improving visual sign language recognition
Proceedings of the 13th annual ACM international conference on Multimedia
A smoothed boosting algorithm using probabilistic output codes
ICML '05 Proceedings of the 22nd international conference on Machine learning
Training Cost-Sensitive Neural Networks with Methods Addressing the Class Imbalance Problem
IEEE Transactions on Knowledge and Data Engineering
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Sharing Classifiers among Ensembles from Related Problem Domains
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Local bagging of decision stumps
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Q2C@UST: our winning solution to query classification in KDDCUP 2005
ACM SIGKDD Explorations Newsletter
Combining heterogeneous classifiers for word-sense disambiguation
WSD '02 Proceedings of the ACL-02 workshop on Word sense disambiguation: recent successes and future directions - Volume 8
Boosting for named entity recognition
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Neural Computation
Machine Learning
Collaborative multi-strategy classification: application to per-pixel analysis of images
MDM '05 Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data
Toward a successful CRM: variable selection, sampling, and ensemble
Decision Support Systems
An ensemble-driven k-NN approach to ill-posed classification problems
Pattern Recognition Letters - Special issue: Pattern recognition in remote sensing (PRRS 2004)
Diversification for better classification trees
Computers and Operations Research
An empirical comparison of supervised learning algorithms
ICML '06 Proceedings of the 23rd international conference on Machine learning
Using query-specific variance estimates to combine Bayesian classifiers
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
Suppressing model overfitting in mining concept-drifting data streams
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining citizen science data to predict orevalence of wild bird species
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Rotation Forest: A New Classifier Ensemble Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
ROC curves and video analysis optimization in intestinal capsule endoscopy
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Demonstrating the stability of support vector machines for classification
Signal Processing - Signal processing in UWB communications
An analysis of diversity measures
Machine Learning
Query enrichment for web-query classification
ACM Transactions on Information Systems (TOIS)
Journal of Biomedical Informatics
A Comparison of Decision Tree Ensemble Creation Techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Feature Selection with Dynamic Integration of Classifiers
Fundamenta Informaticae - Intelligent Systems
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
A Real generalization of discrete AdaBoost
Artificial Intelligence
An empirical study on classification methods for alarms from a bug-finding static C analyzer
Information Processing Letters
Immune network based ensembles
Neurocomputing
Multi-Class Learning by Smoothed Boosting
Machine Learning
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
Multiobjective Optimization in Bioinformatics and Computational Biology
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Decision-tree instance-space decomposition with grouped gain-ratio
Information Sciences: an International Journal
A boosting approach for corporate failure prediction
Applied Intelligence
Pattern Recognition
Ensembles of Neural Networks for Fault Diagnosis in Analog Circuits
Journal of Electronic Testing: Theory and Applications
Authentic facial expression analysis
Image and Vision Computing
Collaborative multi-step mono-level multi-strategy classification
Multimedia Tools and Applications
An experimental evaluation of ensemble methods for EEG signal classification
Pattern Recognition Letters
A comprehensive review of recursive Naïve Bayes Classifiers
Intelligent Data Analysis
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
Dynamic integration of classifiers for handling concept drift
Information Fusion
A framework for agent-based distributed machine learning and data mining
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Machine learning: a review of classification and combining techniques
Artificial Intelligence Review
Expert Systems with Applications: An International Journal
Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks
Decision Support Systems
Risk-sensitive loss functions for sparse multi-category classification problems
Information Sciences: an International Journal
Feature Extraction for Dynamic Integration of Classifiers
Fundamenta Informaticae
Evolutionary multiobjective optimization for the design of fuzzy rule-based ensemble classifiers
International Journal of Hybrid Intelligent Systems - Hybrid Intelligent systems in Ensembles
Constructing ensembles of symbolic classifiers
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
RotBoost: A technique for combining Rotation Forest and AdaBoost
Pattern Recognition Letters
Effective spam filtering: A single-class learning and ensemble approach
Decision Support Systems
AdaBoost with SVM-based component classifiers
Engineering Applications of Artificial Intelligence
A lazy bagging approach to classification
Pattern Recognition
An empirical evaluation of supervised learning in high dimensions
Proceedings of the 25th international conference on Machine learning
Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts
The Journal of Machine Learning Research
Learning classifier system ensemble and compact rule set
Connection Science - Evolutionary Learning and Optimisation
Class-switching neural network ensembles
Neurocomputing
Knowledge transfer via multiple model local structure mapping
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
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
Boosted Bayesian network classifiers
Machine Learning
Coevolutionary bid-based genetic programming for problem decomposition in classification
Genetic Programming and Evolvable Machines
On the Stability and Bias-Variance Analysis of Kernel Matrix Learning
CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Applying Machine Learning Techniques for Detection of Malicious Code in Network Traffic
KI '07 Proceedings of the 30th annual German conference on Advances in Artificial Intelligence
Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble
ECML '07 Proceedings of the 18th European conference on Machine Learning
Ensembles of Multi-Objective Decision Trees
ECML '07 Proceedings of the 18th European conference on Machine Learning
CTC: An Alternative to Extract Explanation from Bagging
Current Topics in Artificial Intelligence
Boosting Threshold Classifiers for High--- Dimensional Data in Functional Genomics
ANNPR '08 Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition
GEP-Induced Expression Trees as Weak Classifiers
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
Towards Heterogeneous Similarity Function Learning for the k-Nearest Neighbors Classification
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Breast Mass Classification on Full-Field Digital Mammography and Screen-Film Mammography
IWDM '08 Proceedings of the 9th international workshop on Digital Mammography
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
An Empirical Study of Combined Classifiers for Knowledge Discovery on Medical Data Bases
Advanced Web and NetworkTechnologies, and Applications
Practical Bias Variance Decomposition
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Combining Bagging, Boosting and Dagging for Classification Problems
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
A Bias-Variance Analysis of Multiple Criteria Linear Programming Classification Ensembles
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Mining Multidimensional Data through Element Oriented Analysis
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Using Boosting to prune Double-Bagging ensembles
Computational Statistics & Data Analysis
The individual borrowers recognition: Single and ensemble trees
Expert Systems with Applications: An International Journal
Empirical analysis of support vector machine ensemble classifiers
Expert Systems with Applications: An International Journal
A selective ensemble based on expected probabilities for bankruptcy prediction
Expert Systems with Applications: An International Journal
Exact bootstrap k-nearest neighbor learners
Machine Learning
Real-Time Road Sign Detection Using Fuzzy-Boosting
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Effective Boosting of Naïve Bayesian Classifiers by Local Accuracy Estimation
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Boosting k-nearest neighbor classifier by means of input space projection
Expert Systems with Applications: An International Journal
Supervised projection approach for boosting classifiers
Pattern Recognition
A New Data-Mining Based Approach for Network Intrusion Detection
CNSR '09 Proceedings of the 2009 Seventh Annual Communication Networks and Services Research Conference
A model-free ensemble method for class prediction with application to biomedical decision making
Artificial Intelligence in Medicine
Heterogeneous source consensus learning via decision propagation and negotiation
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Consensus group stable feature selection
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Classification of DNA microarray data with Random Projection Ensembles of Polynomial SVMs
Proceedings of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008
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
Using Ensemble-Based Reasoning to Help Experts in Melanoma Diagnosis
Proceedings of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence
A Real generalization of discrete AdaBoost
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Stacking for Ensembles of Local Experts in Metabonomic Applications
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Boosting Support Vector Machines Successfully
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Combining Multiple Classifiers with Dynamic Weighted Voting
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Out-of-bag estimation of the optimal sample size in bagging
Pattern Recognition
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Thresholding for making classifiers cost-sensitive
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
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
Several SVM Ensemble Methods Integrated with Under-Sampling for Imbalanced Data Learning
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
On Feature Selection, Bias-Variance, and Bagging
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Learning when training data are costly: the effect of class distribution on tree induction
Journal of Artificial Intelligence Research
Spectrum of variable-random trees
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Decision tree grafting from the all-tests-but-one partition
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
A brief introduction to boosting
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Monte Carlo theory as an explanation of bagging and boosting
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Constructing diverse classifier ensembles using artificial training examples
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Active learning for class probability estimation and ranking
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
The foundations of cost-sensitive learning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
A novel approach to model generation for heterogeneous data classification
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Sequential genetic search for ensemble feature selection
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Automatic identification of music performers with learning ensembles
Artificial Intelligence
Unique classifier selection approach for bagging algorithm
ISC '07 Proceedings of the 10th IASTED International Conference on Intelligent Systems and Control
Exploratory undersampling for class-imbalance learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Image Processing
Constructing ensembles of classifiers by means of weighted instance selection
IEEE Transactions on Neural Networks
Local within-class accuracies for weighting individual outputs in multiple classifier systems
Pattern Recognition Letters
Rotation-based model trees for classification
International Journal of Data Analysis Techniques and Strategies
Ensemble with neural networks for bankruptcy prediction
Expert Systems with Applications: An International Journal
Multiple classifier application to credit risk assessment
Expert Systems with Applications: An International Journal
Zone analysis: a visualization framework for classification problems
Artificial Intelligence Review
A novel ensemble machine learning for robust microarray data classification
Computers in Biology and Medicine
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
Toward a successful CRM: variable selection, sampling, and ensemble
Decision Support Systems
Auto claim fraud detection using Bayesian learning neural networks
Expert Systems with Applications: An International Journal
Stock market trading rule discovery using two-layer bias decision tree
Expert Systems with Applications: An International Journal
Optimal ensemble construction via meta-evolutionary ensembles
Expert Systems with Applications: An International Journal
Artificial Intelligence Review
Naïve Bayes ensemble learning based on oracle selection
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Bagging different instead of similar models for regression and classification problems
International Journal of Computer Applications in Technology
Boosting with pairwise constraints
Neurocomputing
Switching class labels to generate classification ensembles
Pattern Recognition
Ensemble classification based on generalized additive models
Computational Statistics & Data Analysis
CSNL: A cost-sensitive non-linear decision tree algorithm
ACM Transactions on Knowledge Discovery from Data (TKDD)
Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination
The Journal of Machine Learning Research
Feature selection for bagging of support vector machines
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Averaged boosting: a noise-robust ensemble method
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
Naïve Bayes ensembles with a random oracle
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
An experimental study on rotation forest ensembles
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
LCSE: learning classifier system ensemble for incremental medical instances
IWLCS'03-05 Proceedings of the 2003-2005 international conference on Learning classifier systems
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
Error bounds for aggressive and conservative AdaBoost
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
An empirical comparison of three boosting algorithms on real data sets with artificial class noise
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Towards automated classifier combination for pattern recognition
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Multi-category classification by soft-max combination of binary classifiers
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
A sequential scheduling approach to combining multiple object classifiers using cross-entropy
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Combining SVM classifiers for email anti-spam filtering
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Boosting support vector machines using multiple dissimilarities
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Creating ensembles of classifiers via fuzzy clustering and deflection
Fuzzy Sets and Systems
A survey on the application of genetic programming to classification
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
Neural network ensemble training by sequential interaction
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Out of bootstrap estimation of generalization error curves in bagging ensembles
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
On the combination of dissimilarities for gene expression data analysis
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Iterative reordering of rules for building ensembles without relearning
DS'07 Proceedings of the 10th international conference on Discovery science
Ensemble of dissimilarity based classifiers for cancerous samples classification
PRIB'07 Proceedings of the 2nd IAPR international conference on Pattern recognition in bioinformatics
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Selective ensemble of decision trees
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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
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ILP'07 Proceedings of the 17th international conference on Inductive logic programming
On improving discretization quality by a bagging technique
ICNC'09 Proceedings of the 5th international conference on Natural computation
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FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
MALEF: Framework for distributed machine learning and data mining
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Data Mining and Knowledge Discovery
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Intelligent Data Analysis
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Applied Soft Computing
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Applied Intelligence
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NPC'10 Proceedings of the 2010 IFIP international conference on Network and parallel computing
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DILS'10 Proceedings of the 7th international conference on Data integration in the life sciences
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
Mining and post-processing of association rules in the atherosclerosis risk domain
ITBAM'10 Proceedings of the First international conference on Information technology in bio- and medical informatics
Ensemble classification for constraint solver configuration
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
A data mining framework for detecting subscription fraud in telecommunication
Engineering Applications of Artificial Intelligence
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A class-specific ensemble feature selection approach for classification problems
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Random one-dependence estimators
Pattern Recognition Letters
The construction of an individual credit risk assessment method: based on the combination algorithms
ICICA'10 Proceedings of the First international conference on Information computing and applications
An efficient classifier design integrating rough set and set oriented database operations
Applied Soft Computing
Ensemble Learning with Active Example Selection for Imbalanced Biomedical Data Classification
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
An efficient classifier design integrating Rough Set and Dempster-Shafer Theory
International Journal of Artificial Intelligence and Soft Computing
Class imbalance methods for translation initiation site recognition
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
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
Search strategies for ensemble feature selection in medical diagnostics
CBMS'03 Proceedings of the 16th IEEE conference on Computer-based medical systems
Authentic facial expression analysis
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Learning random forests for ranking
Frontiers of Computer Science in China
Combining bagging, boosting, rotation forest and random subspace methods
Artificial Intelligence Review
A synergy of multi-objective optimization and data mining for the analysis of a flexible flow shop
Robotics and Computer-Integrated Manufacturing
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
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction
Expert Systems with Applications: An International Journal
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
Hierarchical annotation of medical images
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Case-based reasoning support for liver disease diagnosis
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Fusion of similarity measures for time series classification
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
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Studying the hybridization of artificial neural networks in HECIC
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Class imbalance methods for translation initiation site recognition in DNA sequences
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A bounded version of online boosting on open-ended data streams
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
Random feature weights for decision tree ensemble construction
Information Fusion
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Empirical study on weighted voting multiple classifiers
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Noisy digit classification with multiple specialist
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ECML'06 Proceedings of the 17th European conference on Machine Learning
Dynamic integration with random forests
ECML'06 Proceedings of the 17th European conference on Machine Learning
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PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
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PCI'05 Proceedings of the 10th Panhellenic conference on Advances in Informatics
Efficient learning by combining confidence-rated classifiers to incorporate unlabeled medical data
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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
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PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Object detection via fusion of global classifier and part-based classifier
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Preference elicitation techniques for group recommender systems
Information Sciences: an International Journal
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ML-CIDIM: multiple layers of multiple classifier systems based on CIDIM
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Clustering and metaclustering with nonnegative matrix decompositions
ECML'05 Proceedings of the 16th European conference on Machine Learning
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
Dynamics of variance reduction in bagging and other techniques based on randomisation
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Inducing diverse decision forests with genetic programming
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Bagging random trees for estimation of tissue softness
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
E-CIDIM: ensemble of CIDIM classifiers
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Robust ensemble learning for cancer diagnosis based on microarray data classification
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Computing confidence measures in stochastic logic programs
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Cascading customized naïve bayes couple
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
A hybrid classification approach to ultrasonic shaft signals
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
Probabilistic ensembles for improved inference in protein-structure determination
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Boosting-based ensemble learning with penalty profiles for automatic Thai unknown word recognition
Computers & Mathematics with Applications
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Balanced boosting with parallel perceptrons
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
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IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
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
Comparing ensembles of learners: detecting prostate cancer from high resolution MRI
CVAMIA'06 Proceedings of the Second ECCV international conference on Computer Vision Approaches to Medical Image Analysis
Probabilistic inference trees for classification and ranking
AI'06 Proceedings of the 19th international conference on Advances in Artificial Intelligence: Canadian Society for Computational Studies of Intelligence
Generalized unified decomposition of ensemble loss
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Weighted bagging for graph based one-class classifiers
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Cut digits classification with k-NN multi-specialist
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Integrated protein interaction networks for 11 microbes
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
Classifiers selection in ensembles using genetic algorithms for bankruptcy prediction
Expert Systems with Applications: An International Journal
Proceedings of the 50th Annual Southeast Regional Conference
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
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ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
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
PISA: A framework for multiagent classification using argumentation
Data & Knowledge Engineering
A model for single and multiple knowledge based networks
Artificial Intelligence in Medicine
An extensive experimental comparison of methods for multi-label learning
Pattern Recognition
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HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
An efficient ensemble classification method based on novel classifier selection technique
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
Biclustering-driven ensemble of Bayesian belief network classifiers for underdetermined problems
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Uniformly subsampled ensemble (USE) for churn management: Theory and implementation
Expert Systems with Applications: An International Journal
Multi-agent based classification using argumentation from experience
Autonomous Agents and Multi-Agent Systems
Intelligible models for classification and regression
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
A few useful things to know about machine learning
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Feature Extraction for Dynamic Integration of Classifiers
Fundamenta Informaticae
Local Feature Selection with Dynamic Integration of Classifiers
Fundamenta Informaticae - Intelligent Systems
ACM Transactions on Asian Language Information Processing (TALIP) - Special Issue on RITE
Intelligent detection computer viruses based on multiple classifiers
UIC'07 Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing
Multi-label ensemble based on variable pairwise constraint projection
Information Sciences: an International Journal
Tree ensembles for predicting structured outputs
Pattern Recognition
Detection of CAN by ensemble classifiers based on ripple down rules
PKAW'12 Proceedings of the 12th Pacific Rim conference on Knowledge Management and Acquisition for Intelligent Systems
New machine learning algorithm: random forest
ICICA'12 Proceedings of the Third international conference on Information Computing and Applications
Efficient protocols for distributed classification and optimization
ALT'12 Proceedings of the 23rd international conference on Algorithmic Learning Theory
A survey of cost-sensitive decision tree induction algorithms
ACM Computing Surveys (CSUR)
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
Bagging ensemble selection for regression
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Defect cluster recognition system for fabricated semiconductor wafers
Engineering Applications of Artificial Intelligence
LBR-Meta: an efficient algorithm for lazy Bayesian rules
AusDM '08 Proceedings of the 7th Australasian Data Mining Conference - Volume 87
Computing precision and recall with missing or uncertain ground truth
GREC'11 Proceedings of the 9th international conference on Graphics Recognition: new trends and challenges
An empirical study of learning from imbalanced data
ADC '11 Proceedings of the Twenty-Second Australasian Database Conference - Volume 115
Artificial Intelligence in Medicine
Empirical study of bagging predictors on medical data
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
Accurate intelligible models with pairwise interactions
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Modelling and Simulation in Engineering
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
On the doubt about margin explanation of boosting
Artificial Intelligence
Feature selection filter for classification of power system operating states
Computers & Mathematics with Applications
Combining supervised and unsupervised models via unconstrained probabilistic embedding
Information Sciences: an International Journal
Learning ensemble classifiers via restricted Boltzmann machines
Pattern Recognition Letters
Sentiment classification: The contribution of ensemble learning
Decision Support Systems
Meta-ELM: ELM with ELM hidden nodes
Neurocomputing
Advanced Engineering Informatics
Artificial Intelligence Review
The impact of multinationality on firm value: A comparative analysis of machine learning techniques
Decision Support Systems
Combining multiple predictive models using genetic algorithms
Intelligent Data Analysis - Combined Learning Methods and Mining Complex Data
IIvotes ensemble for imbalanced data
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Learning to filter spam emails: An ensemble learning approach
International Journal of Hybrid Intelligent Systems
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Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Methods for voting classification algorithms, such as Baggingand AdaBoost, have been shown to be very successful in improving theaccuracy of certain classifiers for artificial and real-worlddatasets. We review these algorithms and describe a large empiricalstudy comparing several variants in conjunction with a decision treeinducer (three variants) and a Naive-Bayes inducer. The purpose ofthe study is to improve our understanding of why and when thesealgorithms, which use perturbation, reweighting, and combinationtechniques, affect classification error. We provide a bias andvariance decomposition of the error to show how different methods andvariants influence these two terms. This allowed us to determinethat Bagging reduced variance of unstable methods, while boostingmethods (AdaBoost and Arc-x4) reduced both the bias and variance ofunstable methods but increased the variance for Naive-Bayes, which was verystable. We observed that Arc-x4 behaves differently than AdaBoost ifreweighting is used instead of resampling, indicating a fundamentaldifference. Voting variants, some of which are introduced in thispaper, include: pruning versus no pruning, use of probabilisticestimates, weight perturbations (Wagging), and backfitting of data.We found that Bagging improves when probabilistic estimates inconjunction with no-pruning are used, as well as when the data wasbackfit. We measure tree sizes and show an interesting positivecorrelation between the increase in the average tree size in AdaBoosttrials and its success in reducing the error. We compare themean-squared error of voting methods to non-voting methods and showthat the voting methods lead to large and significant reductions inthe mean-squared errors. Practical problems that arise inimplementing boosting algorithms are explored, including numericalinstabilities and underflows. We use scatterplots that graphicallyshow how AdaBoost reweights instances, emphasizing not only “hard”areas but also outliers and noise.