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1
Popular Ensemble Methods: An Empirical Study
Popular Ensemble Methods: An Empirical Study
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Popular Ensemble Methods: An Empirical Study

The Journal of artificial intelligence research, , Vol.11, p.169-198 [Peer Reviewed Journal]

1999. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.jair.org/index.php/jair/about ;ISSN: 1076-9757 ;EISSN: 1943-5037 ;DOI: 10.1613/jair.614

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2
Feature selection and effective classifiers
Feature selection and effective classifiers
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Feature selection and effective classifiers

Journal of the American Society for Information Science, 1998, Vol.49 (5), p.423-434

Copyright © 1998 John Wiley & Sons, Inc. ;Copyright Wiley Periodicals Inc. Apr 15, 1998 ;ISSN: 0002-8231 ;EISSN: 1097-4571 ;DOI: 10.1002/(SICI)1097-4571(19980415)49:5<423::AID-ASI5>3.0.CO;2-0

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3
A study in the combination of two consumer credit scores
A study in the combination of two consumer credit scores
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A study in the combination of two consumer credit scores

The Journal of the Operational Research Society, 2001-09, Vol.52 (9), p.974-980 [Peer Reviewed Journal]

Copyright © 2001, Palgrave Publishers Ltd 2001 ;Copyright 2001 Operational Research Society Ltd ;Copyright (c) 2001 Palgrave Publishers Ltd ;ISSN: 0160-5682 ;EISSN: 1476-9360 ;DOI: 10.1057/palgrave.jors.2601225 ;CODEN: OPRQAK

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4
SMOTE: Synthetic Minority Over-sampling Technique
SMOTE: Synthetic Minority Over-sampling Technique
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SMOTE: Synthetic Minority Over-sampling Technique

The Journal of artificial intelligence research, 2002-01, Vol.16, p.321-357 [Peer Reviewed Journal]

2002. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.jair.org/index.php/jair/about ;ISSN: 1076-9757 ;EISSN: 1943-5037 ;DOI: 10.1613/jair.953

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5
A Bayesian framework for the combination of classifier outputs
A Bayesian framework for the combination of classifier outputs
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A Bayesian framework for the combination of classifier outputs

The Journal of the Operational Research Society, 2002-07, Vol.53 (7), p.719-727 [Peer Reviewed Journal]

Copyright © 2002, Palgrave Macmillan Ltd 2002 ;Copyright 2002 Operational Research Society Ltd ;2002 INIST-CNRS ;Copyright (c) 2002 Palgrave Macmillan Ltd ;ISSN: 0160-5682 ;EISSN: 1476-9360 ;DOI: 10.1057/palgrave.jors.2601262 ;CODEN: JORSDZ

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6
Comparison of methodologies for probabilistic quantitative precipitation forecasting
Comparison of methodologies for probabilistic quantitative precipitation forecasting
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Comparison of methodologies for probabilistic quantitative precipitation forecasting

Weather and forecasting, 2002-08, Vol.17 (4), p.783-799 [Peer Reviewed Journal]

2002 INIST-CNRS ;Copyright American Meteorological Society 2002 ;ISSN: 0882-8156 ;EISSN: 1520-0434 ;DOI: 10.1175/1520-0434(2002)017<0783:COMFPQ>2.0.CO;2 ;CODEN: WEFOE3

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7
Meta-Learner for Unknown Attribute Values Processing: Dealing with Inconsistency of Meta-Databases
Meta-Learner for Unknown Attribute Values Processing: Dealing with Inconsistency of Meta-Databases
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Meta-Learner for Unknown Attribute Values Processing: Dealing with Inconsistency of Meta-Databases

Journal of intelligent information systems, 2004-01, Vol.22 (1), p.71 [Peer Reviewed Journal]

Copyright (c) 2004 Kluwer Academic Publishers ;ISSN: 0925-9902 ;EISSN: 1573-7675 ;DOI: 10.1023/A:1025880714026

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8
Sparsity and smoothness via the fused lasso
Sparsity and smoothness via the fused lasso
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Sparsity and smoothness via the fused lasso

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2005-02, Vol.67 (1), p.91-108 [Peer Reviewed Journal]

Copyright 2005 The Royal Statistical Society ;2005 INIST-CNRS ;2005 Royal Statistical Society ;ISSN: 1369-7412 ;EISSN: 1467-9868 ;DOI: 10.1111/j.1467-9868.2005.00490.x

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9
On Data Depth and Distribution-Free Discriminant Analysis Using Separating Surfaces
On Data Depth and Distribution-Free Discriminant Analysis Using Separating Surfaces
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On Data Depth and Distribution-Free Discriminant Analysis Using Separating Surfaces

Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, 2005-02, Vol.11 (1), p.1-27 [Peer Reviewed Journal]

Copyright 2005 International Statistical Institute/Bernoulli Society ;Copyright 2005 Bernoulli Society for Mathematical Statistics and Probability ;ISSN: 1350-7265 ;DOI: 10.3150/bj/1110228239

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10
Improving the prediction of the clinical outcome of breast cancer using evolutionary algorithms
Improving the prediction of the clinical outcome of breast cancer using evolutionary algorithms
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Improving the prediction of the clinical outcome of breast cancer using evolutionary algorithms

Soft computing (Berlin, Germany), 2006-02, Vol.10 (4), p.338-345 [Peer Reviewed Journal]

Springer-Verlag Berlin Heidelberg 2005. ;ISSN: 1432-7643 ;EISSN: 1433-7479 ;DOI: 10.1007/s00500-005-0492-x

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11
Evaluation of methods for reduction of surface texture features
Evaluation of methods for reduction of surface texture features
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Evaluation of methods for reduction of surface texture features

Tribology letters, 2006-05, Vol.22 (2), p.151-165 [Peer Reviewed Journal]

Tribology Letters is a copyright of Springer, (2006). All Rights Reserved. ;ISSN: 1023-8883 ;EISSN: 1573-2711 ;DOI: 10.1007/s11249-006-9067-y

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12
Machine learning: a review of classification and combining techniques
Machine learning: a review of classification and combining techniques
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Machine learning: a review of classification and combining techniques

The Artificial intelligence review, 2006-11, Vol.26 (3), p.159-190 [Peer Reviewed Journal]

Springer Science+Business Media B.V. 2007 ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-007-9052-3

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13
Classification with reject option
Classification with reject option
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Classification with reject option

Canadian journal of statistics, 2006-12, Vol.34 (4), p.709-721 [Peer Reviewed Journal]

Copyright 2006 Statistical Society of Canada / Société statistique du Canada ;Copyright © 2006 Statistical Society of Canada ;Copyright Statistical Society of Canada Dec 2006 ;ISSN: 0319-5724 ;EISSN: 1708-945X ;DOI: 10.1002/cjs.5550340410

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14
Localized Generalization Error of Gaussian-based Classifiers and Visualization of Decision Boundaries
Localized Generalization Error of Gaussian-based Classifiers and Visualization of Decision Boundaries
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Localized Generalization Error of Gaussian-based Classifiers and Visualization of Decision Boundaries

Soft computing (Berlin, Germany), 2007-02, Vol.11 (4), p.375-381 [Peer Reviewed Journal]

Springer-Verlag 2006. ;ISSN: 1432-7643 ;EISSN: 1433-7479 ;DOI: 10.1007/s00500-006-0092-4

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15
Differential prioritization in feature selection and classifier aggregation for multiclass microarray datasets
Differential prioritization in feature selection and classifier aggregation for multiclass microarray datasets
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Differential prioritization in feature selection and classifier aggregation for multiclass microarray datasets

Data mining and knowledge discovery, 2007-06, Vol.14 (3), p.329-366 [Peer Reviewed Journal]

Springer Science+Business Media, LLC 2007 ;Springer Science+Business Media, LLC 2007. ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-006-0055-5

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16
Euk-PLoc: an ensemble classifier for large-scale eukaryotic protein subcellular location prediction
Euk-PLoc: an ensemble classifier for large-scale eukaryotic protein subcellular location prediction
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Euk-PLoc: an ensemble classifier for large-scale eukaryotic protein subcellular location prediction

Amino acids, 2007-07, Vol.33 (1), p.57-67 [Peer Reviewed Journal]

Springer-Verlag 2007. ;ISSN: 0939-4451 ;EISSN: 1438-2199 ;DOI: 10.1007/s00726-006-0478-8 ;PMID: 17235453

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17
Large-Scale Bayesian Logistic Regression for Text Categorization
Large-Scale Bayesian Logistic Regression for Text Categorization
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Large-Scale Bayesian Logistic Regression for Text Categorization

Technometrics, 2007-08, Vol.49 (3), p.291-304 [Peer Reviewed Journal]

American Statistical Association and the American Society for Quality 2007 ;Copyright 2007 The American Statistical Association and The American Society for Quality ;Copyright American Society for Quality Aug 2007 ;ISSN: 0040-1706 ;EISSN: 1537-2723 ;DOI: 10.1198/004017007000000245 ;CODEN: TCMTA2

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18
Evolving Classifiers: Methods for Incremental Learning
Evolving Classifiers: Methods for Incremental Learning
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Evolving Classifiers: Methods for Incremental Learning

arXiv.org, 2007-09

Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the associated terms available at http://arxiv.org/abs/0709.3965. ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.0709.3965

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19
Using artificial neural networks for classification of black-and-white images
Using artificial neural networks for classification of black-and-white images
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Using artificial neural networks for classification of black-and-white images

Cybernetics and systems analysis, 2008-03, Vol.44 (2), p.304-307 [Peer Reviewed Journal]

Springer Science+Business Media, Inc. 2008 ;ISSN: 1060-0396 ;EISSN: 1573-8337 ;DOI: 10.1007/s10559-008-0030-9

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20
Characterization of mammographic masses using a gradient-based segmentation algorithm and a neural classifier
Characterization of mammographic masses using a gradient-based segmentation algorithm and a neural classifier
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Characterization of mammographic masses using a gradient-based segmentation algorithm and a neural classifier

arXiv.org, 2008-03

2008. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.0803.1417

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