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Applying adaptive over-sampling technique based on data density and cost-sensitive SVM to imbalanced learning

https://doi.org/10.1109/ijcnn.2012.6252696
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/11538059_91openalex-snapshot
Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
inferredcites →https://doi.org/10.1007/978-3-540-39804-2_12openalex-snapshot
SMOTEBoost: Improving Prediction of the Minority Class in Boosting
inferredcites →https://doi.org/10.1007/978-3-540-87479-9_34openalex-snapshot
Learning Decision Trees for Unbalanced Data
inferredcites →https://doi.org/10.1007/978-3-540-87732-5_71openalex-snapshot
Imbalanced SVM Learning with Margin Compensation
inferredcites →https://doi.org/10.1007/s00500-010-0625-8openalex-snapshot
Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling
inferredcites →https://doi.org/10.1023/a:1009700419189openalex-snapshot
Adaptive Fraud Detection
inferredcites →https://doi.org/10.1109/iciii.2011.276openalex-snapshot
Applying Over-sampling Technique Based on Data Density and Cost-sensitive SVM to Imbalanced Learning
inferredcites →https://doi.org/10.1109/ijcnn.2008.4633969openalex-snapshot
ADASYN: Adaptive synthetic sampling approach for imbalanced learning
inferredcites →https://doi.org/10.1109/tfuzz.2010.2042721openalex-snapshot
FSVM-CIL: Fuzzy Support Vector Machines for Class Imbalance Learning
inferredcites →https://doi.org/10.1109/tkde.2008.239openalex-snapshot
Learning from Imbalanced Data
inferredcites →https://doi.org/10.1109/tsmcb.2008.2002909openalex-snapshot
SVMs Modeling for Highly Imbalanced Classification
inferredcites →https://doi.org/10.1109/tsmcb.2008.2007853openalex-snapshot
Exploratory Undersampling for Class-Imbalance Learning
inferredcites →https://doi.org/10.1145/1007730.1007735openalex-snapshot
A study of the behavior of several methods for balancing machine learning training data
inferredcites →https://doi.org/10.1145/304182.304187openalex-snapshot
OPTICS
inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot
SMOTE: Synthetic Minority Over-sampling Technique
inferredcites →https://doi.org/10.37052/ml.31(1)no1openalex-snapshot
What's In A Name? Malay Seals As Onomastic Sources

What points at this work

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inferred← citeshttps://doi.org/10.2139/ssrn.4088362openalex-extracted
Stop Oversampling for Class Imbalance Learning: A Critical Approach Review
inferred← citeshttps://doi.org/10.2139/ssrn.4601421openalex-extracted
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inferred← citeshttps://doi.org/10.1002/cem.3515openalex-snapshot
ASER: Adapted squared error relevance for rare cases prediction in imbalanced regression
inferred← citeshttps://doi.org/10.1007/978-3-030-22744-9_14openalex-snapshot
On the Role of Cost-Sensitive Learning in Imbalanced Data Oversampling
inferred← citeshttps://doi.org/10.1007/978-3-030-65299-9_18openalex-snapshot
Push for More: On Comparison of Data Augmentation and SMOTE with Optimised Deep Learning Architecture for Side-Channel
inferred← citeshttps://doi.org/10.1007/978-3-031-73110-5_14openalex-snapshot
Effect of Label-Noise Filtering on Classification of Imbalanced Data Sets with SVM
inferred← citeshttps://doi.org/10.1007/978-3-319-31753-3_11openalex-snapshot
User-Guided Large Attributed Graph Clustering with Multiple Sparse Annotations
inferred← citeshttps://doi.org/10.1007/978-3-319-98074-4_4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s00521-014-1584-2openalex-snapshot
Imbalanced data classification based on scaling kernel-based support vector machine
inferred← citeshttps://doi.org/10.1007/s00521-020-05570-7openalex-snapshot
A novel ensemble method for classification in imbalanced datasets using split balancing technique based on instance hardness (sBal_IH)
inferred← citeshttps://doi.org/10.1007/s10044-020-00890-9openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10115-016-0957-5openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.asoc.2019.105662openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.neucom.2018.11.099openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.neunet.2015.06.005openalex-snapshot
Near-Bayesian Support Vector Machines for imbalanced data classification with equal or unequal misclassification costs
inferred← citeshttps://doi.org/10.1016/j.patcog.2017.12.017openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2021.3074243openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2021.3081366openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2022.3169512openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/bigdatacongress.2017.70openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/cgc.2012.79openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icic54025.2021.9632912openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/ictai.2012.164openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/iscc58397.2023.10218211openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/qrs60937.2023.00014openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tcad.2015.2413840openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tits.2018.2870948openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tkde.2017.2682249openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tnnls.2018.2869298openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tnnls.2022.3177695openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tpami.2018.2832629openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3357384.3357962openalex-snapshot
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inferred← citeshttps://doi.org/10.1155/2014/972786openalex-snapshot
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inferred← citeshttps://doi.org/10.12794/metadc407775openalex-snapshot
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inferred← citeshttps://doi.org/10.1371/journal.pone.0317396openalex-snapshot
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inferred← citeshttps://doi.org/10.14569/ijacsa.2025.01603105openalex-snapshot
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inferred← citeshttps://doi.org/10.1609/aaai.v32i1.11761openalex-snapshot
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inferred← citeshttps://doi.org/10.1613/jair.1.11192openalex-snapshot
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inferred← citeshttps://doi.org/10.17559/tv-20180203105331openalex-snapshot
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inferred← citeshttps://doi.org/10.17671/gazibtd.1019015openalex-snapshot
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inferred← citeshttps://doi.org/10.21203/rs.3.rs-1336037/v1openalex-snapshot
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inferred← citeshttps://doi.org/10.25126/jtiik.1067325openalex-snapshot
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inferred← citeshttps://doi.org/10.31142/ijtsrd21574openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/app10030973openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/app12094726openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/jmse12101817openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/s22093121openalex-snapshot
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inferred← citeshttps://doi.org/10.35940/ijeat.d7349.049420openalex-snapshot
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inferred← citeshttps://doi.org/10.3844/jcssp.2019.886.929openalex-snapshot
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inferred← citeshttps://doi.org/10.4304/jcp.9.2.483-490openalex-snapshot
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inferred← citeshttps://doi.org/10.48550/arxiv.1910.08489openalex-snapshot
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inferred← citeshttps://doi.org/10.5121/ijci.2023.120607openalex-snapshot
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inferred← citeshttps://doi.org/10.5121/ijdps.2017.8100openalex-snapshot
inferred← citeshttps://doi.org/10.5121/ijdps.2017.8200openalex-snapshot
inferred← citeshttps://doi.org/10.5121/ijdps.2017.8301openalex-snapshot
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inferred← citeshttps://doi.org/10.58837/chula.the.2019.11openalex-snapshot
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inferred← citeshttps://doi.org/10.70675/8189248bzf497z4610zb76aza9883673aeb8openalex-snapshot
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