关键词: 孤立点检测, 凝聚层次聚类, 径向基神经网络, 预测

Abstract: Propose a new agglomerative hierarchical clustering based method to eliminate outliers，with clustering tree to identify outliers.After removing the outliers，build a dynamic prediction model by RBF network，and the experimental results show that the training and generalization performance are markedly improved，which means the agglomerative hierarchical clustering method is effective and workable for outlier detection.After the elimination of outliers，the model shows faster converging speed and higher generalization ability.

Key words: outlier detection, agglomerative hierarchical clustering, radial basis function neural network, prediction