Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper.
Query: Clustering-based undersampling in class-imbalanced data
Coupling different methods for overcoming the class imbalance problem
Dealing with multiple classes in online class imbalance learning
Learning from Imbalanced Data
A Comparison of External Clustering Evaluation Indices in the Context of Imbalanced Data Sets
RHSBoost: Improving classification performance in imbalance data
Extending Bagging for Imbalanced Data
Handling imbalanced datasets: A review
AdaOUBoost: adaptive over-sampling and under-sampling to boost the concept learning in large scale imbalanced data sets
Distributional Random Oversampling for Imbalanced Text Classification
Absent data generating classifier for imbalanced class sizes
Feature Selection in Imbalance data sets
Learning from imbalanced data: open challenges and future directions
Experimental perspectives on learning from imbalanced data
Probability density function estimation based over-sampling for imbalanced two-class problems
Classification with class imbalance problem: a review
A Novel Data Representation for Effective Learning in Class Imbalanced Scenarios
Distance Metric Based Oversampling Method for Bioinformatics and Performance Evaluation
A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets.
Using Random Forest to Learn Imbalanced Data
A Novel Ensemble Method for Imbalanced Data Learning: Bagging of Extrapolation-SMOTE SVM
Fully-functional succinct trees
Location-Aware Image Classification
From genes to behavior in developmental dyslexia
RAMOBoost: Ranked Minority Oversampling in Boosting
servicescapes , trust , and purchase intentions .