4 papers
Finding Time Series Anomalies using Granular-ball Vector Data Description
Lifeng Shen, Liang Peng, Ruiwen Liu +2
Modeling normal behavior in dynamic, nonlinear time series data is challenging for effective anomaly detection. Traditional methods, such as nearest neighbor and clustering approac…
GAdaBoost: An Efficient and Robust AdaBoost Algorithm Based on Granular-Ball Structure
Qin Xie, Qinghua Zhang, Shuyin Xia +2
Adaptive Boosting (AdaBoost) faces significant challenges posed by label noise, especially in multiclass classification tasks. Existing methods either lack mechanisms to handle lab…
Approximate Borderline Sampling using Granular-Ball for Classification Tasks
Qin Xie, Qinghua Zhang, Shuyin Xia
Data sampling enhances classifier efficiency and robustness through data compression and quality improvement. Recently, the sampling method based on granular-ball (GB) has shown pr…
EvoSampling: A Granular Ball-based Evolutionary Hybrid Sampling with Knowledge Transfer for Imbalanced Learning
Wenbin Pei, Ruohao Dai, Bing Xue +4
Class imbalance would lead to biased classifiers that favor the majority class and disadvantage the minority class. Unfortunately, from a practical perspective, the minority class…