Who Cited It

An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics

2013 · Information Sciences · 1,602 citations · 5 from inside this corpus

Victoria López, Alberto Fernández, Salvador García, Vasile Palade, Francisco Herrera

No abstract in the source record.

An insight into classification with imbalanced data: Empirical results and current trends… (2013)An insight into classificatio…Support-vector networks (1995)Support-vector networksSupport-Vector Networks (1995)Support-Vector NetworksSMOTE: Synthetic Minority Over-sampling Technique (2002)SMOTE: Synthetic Minority Ove…C4.5: Programs for Machine Learning (1992)C4.5: Programs for Machine Le…Modern Information Retrieval (1999)Modern Information RetrievalLearning from Imbalanced Data (2009)Learning from Imbalanced DataThe use of the area under the ROC curve in the evaluation of machine learning algorithms (1997)The use of the area under the…Proceedings of the 25th international conference on Machine learning - ICML '08 (2008)Proceedings of the 25th inter…The relationship between Precision-Recall and ROC curves (2006)The relationship between Prec…Advances in kernel methods: support vector learning (1999)Advances in kernel methods: s…ADASYN: Adaptive synthetic sampling approach for imbalanced learning (2008)ADASYN: Adaptive synthetic sa…A study of the behavior of several methods for balancing machine learning training data (2004)A study of the behavior of se…Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning (2005)Borderline-SMOTE: A New Over-…The class imbalance problem: A systematic study1 (2002)The class imbalance problem: …Ensemble based systems in decision making (2006)Ensemble based systems in dec…A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Ba… (2011)A Review on Ensembles for the…Exploratory Undersampling for Class-Imbalance Learning (2008)Exploratory Undersampling for…Using AUC and accuracy in evaluating learning algorithms (2005)Using AUC and accuracy in eva…Editorial (2004)EditorialRUSBoost: A Hybrid Approach to Alleviating Class Imbalance (2009)The foundations of cost-sensitive learning (2001)CLASSIFICATION OF IMBALANCED DATA: A REVIEW (2009)CLASSIFICATION OF IMBALANCED …SMOTEBoost: Improving Prediction of the Minority Class in Boosting (2003)SMOTEBoost: Improving Predict…KEEL: a software tool to assess evolutionary algorithms for data mining problems (2008)KEEL: a software tool to asse…Cost-sensitive boosting for classification of imbalanced data (2007)Cost-sensitive boosting for c…Mining with rarity (2004)Mining with rarityLearning from imbalanced data: open challenges and future directions (2016)Learning from imbalanced data…Learning from class-imbalanced data: Review of methods and applications (2016)Learning from class-imbalance…Classification assessment methods (2018)Classification assessment met…SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Ann… (2018)SMOTE for Learning from Imbal…Deep Learning Applications in Medical Image Analysis (2017)Deep Learning Applications in…
31 of 31 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Support-vector networks199541,028
Support-Vector Networks199533,914
SMOTE: Synthetic Minority Over-sampling Technique200232,402
C4.5: Programs for Machine Learning199223,704
Modern Information Retrieval199911,572
Learning from Imbalanced Data200910,209
The use of the area under the ROC curve in the evaluation of machine learning algorithms19977,328
Proceedings of the 25th international conference on Machine learning - ICML '0820086,718
The relationship between Precision-Recall and ROC curves20066,427
Advances in kernel methods: support vector learning19995,819
ADASYN: Adaptive synthetic sampling approach for imbalanced learning20084,556
A study of the behavior of several methods for balancing machine learning training data20044,222
Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning20054,049
The class imbalance problem: A systematic study120023,353
Ensemble based systems in decision making20062,965
A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Ba…20112,834
Exploratory Undersampling for Class-Imbalance Learning20082,504
Using AUC and accuracy in evaluating learning algorithms20052,163
Editorial20042,081
RUSBoost: A Hybrid Approach to Alleviating Class Imbalance20091,890
The foundations of cost-sensitive learning20011,837
CLASSIFICATION OF IMBALANCED DATA: A REVIEW20091,713
SMOTEBoost: Improving Prediction of the Minority Class in Boosting20031,680
KEEL: a software tool to assess evolutionary algorithms for data mining problems20081,508
Cost-sensitive boosting for classification of imbalanced data20071,438
Mining with rarity20041,396

What cites it, inside the corpus

PaperYearCited
Learning from imbalanced data: open challenges and future directions20162,489
Learning from class-imbalanced data: Review of methods and applications20162,407
Classification assessment methods20182,377
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Ann…20182,226
Deep Learning Applications in Medical Image Analysis20171,497

Links

DOI · OpenAlex record

Topics

Imbalanced Data Classification TechniquesComputer Science
Electricity Theft Detection TechniquesEngineering
Machine Learning and Data ClassificationComputer Science

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complete

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  • supports5 author record(s) attached.
  • supports192 reference(s) recorded.
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  • supportsA title is present.

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