Abstract:Many knernel density estimation (KDE)-based data classification methods ignore class imbalance problem.
Therefore, the improved KDE-based data classification algorithm is proposed, which can enable KDE-based classifier
to have good prediction ability under that bad condition. Moreover, this improvement can be extended to multi-class
classification. Experiment results show the effectiveness of the improvement.