• ADASYN

  • Referenced in 19 articles [sw36457]
  • ADASYN: Adaptive synthetic sampling approach for imbalanced learning. This paper presents a novel adaptive synthetic ... ADASYN) sampling approach for learning from imbalanced data sets. The essential idea of ADASYN ... according to their level of difficulty in learning, where more synthetic data is generated...
  • MWMOTE

  • Referenced in 14 articles [sw32596]
  • Oversampling Technique for Imbalanced Data Set Learning. Imbalanced learning problems contain an unequal distribution ... minority samples in some scenarios and make learning tasks harder. To this ... MWMOTE), is presented for efficiently handling imbalanced learning problems. MWMOTE first identifies the hard...
  • Imbalanced-learn

  • Referenced in 10 articles [sw21535]
  • Imbalanced-learn: a python toolbox to tackle the curse of imbalanced datasets in machine learning ... imbalanced-learn is an open-source python toolbox aiming at providing a wide range ... with the problem of imbalanced dataset frequently encountered in machine learning and pattern recognition...
  • RUSBoost

  • Referenced in 5 articles [sw20607]
  • improving classification performance when training data is imbalanced. In addition to performing favorably when compared ... makes RUSBoost an excellent technique for learning from imbalanced data...
  • ROSEFW-RF

  • Referenced in 3 articles [sw23974]
  • extremely imbalanced big data bioinformatics problem. The application of data mining and machine learning techniques ... collect representative positive examples. Learning under these circumstances, known as imbalanced big data classification...
  • hyperSMURF

  • Referenced in 0 articles [sw16396]
  • learning supervised method to learn rare genomic features in imbalanced genetic data sets. This method ... oversampling of the minority class to learn highly imbalanced data. Both single-core and parallel...
  • IRIC

  • Referenced in 2 articles [sw32593]
  • classification. Imbalanced classification is a challenging issue in data mining and machine learning, for which ... integrates a wide set of solutions for imbalanced binary classification. IRIC not only provides...
  • ImbTreeEntropy

  • Referenced in 2 articles [sw40352]
  • gain. Additionally, ImbTreeEntropy is able to handle imbalanced data, which is a challenging issue ... practical applications. The package supports cost-sensitive learning by defining a misclassification cost matrix...
  • ImbTreeAUC

  • Referenced in 2 articles [sw40353]
  • global AUC measures. Additionally, ImbTreeAUC can handle imbalanced data, which is a challenging issue ... practical applications. The package supports cost-sensitive learning by defining a misclassification cost matrix...
  • extended_rmcv.m

  • Referenced in 2 articles [sw34281]
  • based BNC is superior to BNCs learned using the other measures -- especially for ordinal classification ... error severity is important) and/or imbalanced problems (which are most real-life classification problems...
  • Multi-imbalance

  • Referenced in 1 article [sw33185]
  • relatively mature nowadays, yet multi-class imbalance learning is still an open problem. Moreover ... imbalanced data classification. It provides users with seven different categories of multi-class imbalance learning...
  • ivadomed

  • Referenced in 1 article [sw35828]
  • tedious task. Beyond the traditional deep learning methods, ivadomed features cutting-edge architectures, such ... aleatoric and epistemic), and losses adapted to imbalanced classes and non-binary predictions. Each step ... exploration of the latest advances in deep learning for medical imaging applications...
  • AUC4.5

  • Referenced in 1 article [sw40358]
  • modification of Quinlan’s C4.5 algorithm for imbalanced data classification. While the C4.5 algorithm uses ... real datasets from the machine learning repository at the University of California at Irvine, Irvine...
  • Maple

  • Referenced in 5369 articles [sw00545]
  • The result of over 30 years of cutting...
  • MapReduce

  • Referenced in 263 articles [sw00546]
  • MapReduce is a new parallel programming model initially...
  • Matlab

  • Referenced in 13488 articles [sw00558]
  • MATLAB® is a high-level language and interactive...
  • mclust

  • Referenced in 308 articles [sw00563]
  • R package mclust: Normal Mixture Modeling for Model...
  • R

  • Referenced in 9832 articles [sw00771]
  • R is a language and environment for statistical...
  • RFCM

  • Referenced in 8 articles [sw02668]
  • RFCM: a hybrid clustering algorithm using rough and...