Neural networks and the bias/variance dilemma
Neural Computation
C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning - Special issue on learning with probabilistic representations
Distributional clustering of words for text classification
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Learning to classify text from labeled and unlabeled documents
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Empirical Data Modeling in Software Engineering Using Radial Basis Functions
IEEE Transactions on Software Engineering
Computational Economics - Computational Studies at Stanford
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
MultiBoosting: A Technique for Combining Boosting and Wagging
Machine Learning
Technical Note: Naive Bayes for Regression
Machine Learning
Class discovery in gene expression data
RECOMB '01 Proceedings of the fifth annual international conference on Computational biology
An efficient and scalable data compression approach to classification
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Using Iterated Bagging to Debias Regressions
Machine Learning
Data mining by attribute decomposition with semiconductor manufacturing case study
Data mining for design and manufacturing
Bayesian Networks for Data Mining
Data Mining and Knowledge Discovery
The Role of Occam‘s Razor in Knowledge Discovery
Data Mining and Knowledge Discovery
Bootstrapping to Assess and Improve Atmospheric Prediction Models
Data Mining and Knowledge Discovery
Support Vector Machines and the Bayes Rule in Classification
Data Mining and Knowledge Discovery
Bump hunting in high-dimensional data
Statistics and Computing
Looking for lumps: boosting and bagging for density estimation
Computational Statistics & Data Analysis - Nonlinear methods and data mining
Understanding Probabilistic Classifiers
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Some Enhencements of Decision Tree Bagging
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
Improving Supervised Learning by Feature Decomposition
FoIKS '02 Proceedings of the Second International Symposium on Foundations of Information and Knowledge Systems
Bagging Can Stabilize without Reducing Variance
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Conditionally Independent Component Extraction for Naive Bayes Inference
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
An Efficient Data Compression Approach to the Classification Task
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Augmenting Supervised Neural Classifier Training Using a Corpus of Unlabeled Data
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
Bias-Variance Analysis and Ensembles of SVM
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Cooperative Case Bartering for Case-Based Reasoning Agents
CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
CAIP '01 Proceedings of the 9th International Conference on Computer Analysis of Images and Patterns
Toward a Computational Theory of Data Acquisition and Truthing
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
The VLDB Journal — The International Journal on Very Large Data Bases
Enhanced word clustering for hierarchical text classification
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Customer lifetime value modeling and its use for customer retention planning
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Knowledge discovery in databases: the purpose, necessity, and challenges
Handbook of data mining and knowledge discovery
Data mining tasks and methods: Classification: Bayesian classification
Handbook of data mining and knowledge discovery
Data mining tasks and methods: Classification: nearest-neighbor approaches
Handbook of data mining and knowledge discovery
Handbook of data mining and knowledge discovery
Data mining for hypertext: a tutorial survey
ACM SIGKDD Explorations Newsletter
Learning to form dynamic committees
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
An introduction to boosting and leveraging
Advanced lectures on machine learning
Intelligent data analysis
A divisive information theoretic feature clustering algorithm for text classification
The Journal of Machine Learning Research
Tree induction vs. logistic regression: a learning-curve analysis
The Journal of Machine Learning Research
Facial expression recognition from video sequences: temporal and static modeling
Computer Vision and Image Understanding - Special issue on Face recognition
Active Sampling for Class Probability Estimation and Ranking
Machine Learning
Semi-supervised learning for facial expression recognition
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
Instance-Based Regression by Partitioning Feature Projections
Applied Intelligence
Learning Bayesian network classifiers by maximizing conditional likelihood
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model Averaging for Prediction with Discrete Bayesian Networks
The Journal of Machine Learning Research
Kernel density classification and boosting: an L2 analysis
Statistics and Computing
A hierarchical naive Bayes mixture model for name disambiguation in author citations
Proceedings of the 2005 ACM symposium on Applied computing
On Visualization and Aggregation of Nearest Neighbor Classifiers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Closed-form dual perturb and combine for tree-based models
ICML '05 Proceedings of the 22nd international conference on Machine learning
The case for anomalous link discovery
ACM SIGKDD Explorations Newsletter
Conditional structure versus conditional estimation in NLP models
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Nonparametric Supervised Learning by Linear Interpolation with Maximum Entropy
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Classification using Hierarchical Naïve Bayes models
Machine Learning
Classification-based objective functions
Machine Learning
Confidence-Based Active Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Swarm bias-variance analysis of an evolutionary neural network classifier
AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
Effective and efficient classification on a search-engine model
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Performance thresholding in practical text classification
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Some Equivalences between Kernel Methods and Information Theoretic Methods
Journal of VLSI Signal Processing Systems
Confidence-based classifier design
Pattern Recognition
Feature set decomposition for decision trees
Intelligent Data Analysis
Prediction in Marketing Using the Support Vector Machine
Marketing Science
Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation
The Journal of Machine Learning Research
Discovering and Exploiting Causal Dependencies for Robust Mobile Context-Aware Recommenders
IEEE Transactions on Knowledge and Data Engineering
On the Bayes fusion of visual features
Image and Vision Computing
Classifier ensembles: Select real-world applications
Information Fusion
IEEE Transactions on Knowledge and Data Engineering
Modeling consumer situational choice of long distance communication with neural networks
Decision Support Systems
RotBoost: A technique for combining Rotation Forest and AdaBoost
Pattern Recognition Letters
Cost-sensitive multi-class classification from probability estimates
Proceedings of the 25th international conference on Machine learning
A critical analysis of variants of the AUC
Machine Learning
Effective and efficient classification on a search-engine model
Knowledge and Information Systems
A bias/variance decomposition for models using collective inference
Machine Learning
Boosted Bayesian network classifiers
Machine Learning
Classification in Very High Dimensional Problems with Handfuls of Examples
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Discriminative Structure Learning of Markov Logic Networks
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Ranking the Uniformity of Interval Pairs
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Naive Bayes for optimal ranking
Journal of Experimental & Theoretical Artificial Intelligence
Local reweight wrapper for the problem of imbalance
International Journal of Artificial Intelligence and Soft Computing
Handling imbalanced data sets with a modification of Decorate algorithm
International Journal of Computer Applications in Technology
Bagging, Random Subspace Method and Biding
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Bayesian classifiers based on kernel density estimation: Flexible classifiers
International Journal of Approximate Reasoning
Class dependent feature scaling method using naive Bayes classifier for text datamining
Pattern Recognition Letters
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Active Feature-Value Acquisition
Management Science
Searching for interacting features in subset selection
Intelligent Data Analysis
Improved Uniformity Enforcement in Stochastic Discrimination
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data
Generalised indirect classifiers
Computational Statistics & Data Analysis
Confidence intervals for probabilistic network classifiers
Computational Statistics & Data Analysis
IEEE Transactions on Image Processing
Selective costing ensemble for handling imbalanced data sets
International Journal of Hybrid Intelligent Systems
On the size of a classification tree
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
Evaluation of expression recognition techniques
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Weighted proportional k-interval discretization for naive-Bayes classifiers
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
1BC2: a true first-order Bayesian classifier
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Statistical inference of minimum BD estimators and classifiers for varying-dimensional models
Journal of Multivariate Analysis
Stop wasting time: on predicting the success or failure of learning for industrial applications
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Cooperative multiagent learning
Adaptive agents and multi-agent systems
Transfer learning through indirect encoding
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge
INFORMS Journal on Computing
Edited AdaBoost by weighted kNN
Neurocomputing
A tree augmented classifier based on Extreme Imprecise Dirichlet Model
International Journal of Approximate Reasoning
Leveraging bagging for evolving data streams
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Invariant operators, small samples, and the bias-variance dilemma
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Active learning from stream data using optimal weight classifier ensemble
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Bayesian multiscale smoothing in supervised and semi-supervised kernel discriminant analysis
Computational Statistics & Data Analysis
A design of analysis model using feature weighting on CBR method
ROCOM'06 Proceedings of the 6th WSEAS international conference on Robotics, control and manufacturing technology
Instance-based classifiers applied to medical databases: Diagnosis and knowledge extraction
Artificial Intelligence in Medicine
Hybrid parallel classifiers for semantic subspace learning
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
Acquiring knowledge about human goals from Search Query Logs
Information Processing and Management: an International Journal
A Bayesian network classifier that combines a finite mixture model and a naïve bayes model
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Using OVA modeling to improve classification performance for large datasets
Expert Systems with Applications: An International Journal
To select or to weigh: a comparative study of model selection and model weighing for SPODE ensembles
ECML'06 Proceedings of the 17th European conference on Machine Learning
Weighted average pointwise mutual information for feature selection in text categorization
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Assigning function tags with a simple model
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Techniques for improving the performance of naive bayes for text classification
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Dynamics of variance reduction in bagging and other techniques based on randomisation
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Supervised subspace projections for constructing ensembles of classifiers
Information Sciences: an International Journal
Tomographic considerations in ensemble bias/variance decomposition
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Predictive analytics in information systems research
MIS Quarterly
Bayesian learning for cardiac SPECT image interpretation
Artificial Intelligence in Medicine
A fast subspace text categorization method using parallel classifiers
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part II
A novel algorithm applied to classify unbalanced data
Applied Soft Computing
International Journal of Artificial Intelligence and Soft Computing
An analysis of how ensembles of collective classifiers improve predictions in graphs
Proceedings of the 21st ACM international conference on Information and knowledge management
Bagging and Boosting statistical machine translation systems
Artificial Intelligence
A Multi-Expert System for chlorine electrolyzer monitoring
Expert Systems with Applications: An International Journal
A survey on smartphone-based systems for opportunistic user context recognition
ACM Computing Surveys (CSUR)
The Journal of Machine Learning Research
Positive-versus-Negative Classification for Model Aggregation in Predictive Data Mining
INFORMS Journal on Computing
A MapReduce-based distributed SVM ensemble for scalable image classification and annotation
Computers & Mathematics with Applications
Control-flow integrity principles, implementations, and applications
ACM Transactions on Information and System Security (TISSEC)
Credal ensembles of classifiers
Computational Statistics & Data Analysis
Hybrid classifiers based on semantic data subspaces for two-level text categorization
International Journal of Hybrid Intelligent Systems
A two-phase hybrid of semi-supervised and active learning approach for sequence labeling
Intelligent Data Analysis
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The classification problem is considered in which an outputvariable y assumes discrete values with respectiveprobabilities that depend upon the simultaneous values of a set of input variablesx = {x_1,....,x_n}. At issue is how error in the estimates of theseprobabilities affects classification error when the estimates are used ina classification rule. These effects are seen to be somewhat counterintuitive in both their strength and nature. In particular the bias andvariance components of the estimation error combine to influenceclassification in a very different way than with squared error on theprobabilities themselves. Certain types of (very high) bias can becanceled by low variance to produce accurate classification. This candramatically mitigate the effect of the bias associated with some simpleestimators like “naive” Bayes, and the bias induced by thecurse-of-dimensionality on nearest-neighbor procedures. This helps explainwhy such simple methods are often competitive with and sometimes superiorto more sophisticated ones for classification, and why“bagging/aggregating” classifiers can often improveaccuracy. These results also suggest simple modifications to theseprocedures that can (sometimes dramatically) further improve theirclassification performance.