Majority data-based overlapping shift technique for imbalanced datasets classification with small disjuncts and outliers.

Semi-supervised Kernel Fisher discriminant analysis based on exponential-adjusted geometric distance.

A MeanShift-guided oversampling with self-adaptive sizes for imbalanced data classification.

Heterogeneous teaching-learning based optimization with local search for the covering delivering problem in last mile delivery.

Self-adaptive oversampling method based on the complexity of minority data in imbalanced datasets classification.

Regularized semi-supervised KLFDA algorithm based on density peak clustering.

SVDD-based weighted oversampling technique for imbalanced and overlapped dataset learning.

Fitness peak clustering based dynamic multi-swarm particle swarm optimization with enhanced learning strategy.

SVDD boundary and DPC clustering technique-based oversampling approach for handling imbalanced and overlapped data.

The ensemble of density-sensitive SVDD classifier based on maximum soft margin for imbalanced datasets.

Self-Adaptive two roles hybrid learning strategies-based particle swarm optimization.

Density peak clustering using global and local consistency adjustable manifold distance.

Affinity and class probability-based fuzzy support vector machine for imbalanced data sets.

Adaptive weighted over-sampling for imbalanced datasets based on density peaks clustering with heuristic filtering.

Multiple scale self-adaptive cooperation mutation strategy-based particle swarm optimization.

Spectral clustering algorithm using density-sensitive distance measure with global and local consistencies.

Density-sensitive fuzzy kernel maximum entropy clustering algorithm.

Self-adaptive cost weights-based support vector machine cost-sensitive ensemble for imbalanced data classification.

Density-sensitive Robust Fuzzy Kernel Principal Component Analysis technique.

Real-value negative selection over-sampling for imbalanced data set learning.