Qi Kang

A Noise-Filtered Under-Sampling Scheme for Imbalanced Classification

2016 · IEEE Transactions on Cybernetics

Under-sampling is a popular data preprocessing method in dealing with class imbalance problems, with the purposes of balancing datasets to achieve a high classification rate and avoiding the bias toward majority class examples. It always …

An Adaptive Pre-clustering Support Vector Machine for Binary Imbalanced Classification

2018

Imbalance classification is a common but critical problem in machine learning and artificial intelligence. Derived from structural risk minimization, a Support Vector Machine (SVM) enjoys great reputation in classification. However, the original SVM is not …

An Analysis on the Blended Teaching Reform on English Oral Courses

2019 · Proceedings of the 2019 3rd International Seminar on Education, Management and Social Sciences (ISEMSS 2019)

With the development of information technology in the recent decades, the higher educational institutions in China are facing challenges to undertake educational reforms. It is necessary for universities to fulfill the tasks of instilling knowledge …

Class Incremental Learning via Feature Knowledge Prompts

2025

Incremental learning uses previous knowledge and experience to deal with new problems. Traditional class incremental Learning methods usually need to ensure the current model's sensitivity to old tasks by storing, retrieving and using a large …