The Strength of Weak Learnability
Machine Learning
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
On the Accuracy of Meta-learning for Scalable Data Mining
Journal of Intelligent Information Systems
An Efficient Method To Estimate Bagging‘s Generalization Error
Machine Learning
A Survey of Methods for Scaling Up Inductive Algorithms
Data Mining and Knowledge Discovery
Incremental Induction of Decision Trees
Machine Learning
SPRINT: A Scalable Parallel Classifier for Data Mining
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Scaling up: distributed machine learning with cooperation
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
MobiMine: monitoring the stock market from a PDA
ACM SIGKDD Explorations Newsletter
Distributed learning with bagging-like performance
Pattern Recognition Letters
Some Enhencements of Decision Tree Bagging
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Iteratively Selecting Feature Subsets for Mining from High-Dimensional Databases
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
How Can Computer Science Contribute to Knowledge Discovery?
SOFSEM '01 Proceedings of the 28th Conference on Current Trends in Theory and Practice of Informatics Piestany: Theory and Practice of Informatics
Racing Committees for Large Datasets
DS '02 Proceedings of the 5th International Conference on Discovery Science
Efficient Data Mining by Active Learning
Progress in Discovery Science, Final Report of the Japanese Discovery Science Project
Distributed Pasting of Small Votes
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
Revised Papers from Large-Scale Parallel Data Mining, Workshop on Large-Scale Parallel KDD Systems, SIGKDD
IEEE Transactions on Knowledge and Data Engineering
Learning Ensembles from Bites: A Scalable and Accurate Approach
The Journal of Machine Learning Research
Genetic programming in classifying large-scale data: an ensemble method
Information Sciences: an International Journal - Special issue: Soft computing data mining
DXCS: an XCS system for distributed data mining
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Ensembles of biased classifiers
ICML '05 Proceedings of the 22nd international conference on Machine learning
Intelligent vocal cord image analysis for categorizing laryngeal diseases
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Multiple feature sets based categorization of laryngeal images
Computer Methods and Programs in Biomedicine
Distributed classification in peer-to-peer networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Cascade RSVM in Peer-to-Peer Networks
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Out-of-bag estimation of the optimal sample size in bagging
Pattern Recognition
Computational Statistics & Data Analysis
Ensembles of Abstaining Classifiers Based on Rule Sets
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Communication-Efficient Classification in P2P Networks
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Artificial Intelligence Review
Towards incremental classifier fusion
Intelligent Data Analysis
Boosting lite: handling larger datasets and slower base classifiers
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Ensemble techniques for parallel genetic programming based classifiers
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
A new ensemble diversity measure applied to thinning ensembles
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Incremental learning with multiple classifier systems using correction filters for classification
IDA'07 Proceedings of the 7th international conference on Intelligent data analysis
Integrating selective pre-processing of imbalanced data with Ivotes ensemble
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Computer aided diagnosis of Alzheimer's disease using component based SVM
Applied Soft Computing
Incremental learning with multi-level adaptation
Neurocomputing
Estimation of optimal sample size of decision forest with SVM using embedded cross-validation method
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
MCS'11 Proceedings of the 10th international conference on Multiple classifier systems
Variable consistency bagging ensembles
Transactions on Rough Sets XI
Adaptive ensemble classification in p2p networks
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Satrap: data and network heterogeneity aware P2P data-mining
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Evolutionary adapted ensemble for reoccurring context
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Predicting shellfish farm closures with class balancing methods
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Ensemble classifier generation using non-uniform layered clustering and Genetic Algorithm
Knowledge-Based Systems
Dynamic multi-objective evolution of classifier ensembles for video face recognition
Applied Soft Computing
A survey on concept drift adaptation
ACM Computing Surveys (CSUR)
Peer-to-peer data mining classifiers for decentralized detection of network attacks
ADC '13 Proceedings of the Twenty-Fourth Australasian Database Conference - Volume 137
Classification in P2P networks with cascade support vector machines
ACM Transactions on Knowledge Discovery from Data (TKDD)
IIvotes ensemble for imbalanced data
Intelligent Data Analysis - Combined Learning Methods and Mining Complex Data
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Many databases have grown to the point where they cannot fit into the fast memory of even large memory machines, to say nothing of current workstations. If what we want to do is to use these data bases to construct predictions of various characteristics, then since the usual methods require that all data be held in fast memory, various work-arounds have to be used. This paper studies one such class of methods which give accuracy comparable to that which could have been obtained if all data could have been held in core and which are computationally fast. The procedure takes small pieces of the data, grows a predictor on each small piece and then pastes these predictors together. A version is given that scales up to terabyte data sets. The methods are also applicable to on-line learning.