A New Isolated Point Detecting Algorithm Based on Statistical Clustering RBF Neural Network
基于统计聚类RBF神经网络的孤立点检测研究

Mining isolated point is an important field in Data Mining. Methods of statistical analysis have natural advantage in detecting isolated points. In this paper, statistical clustering is first integrated into RBF Neural Network and a new isolated point detecting algorithm based on statistical clustering RBF Neural Network, SCRRBF is proposed, which has two steps. The first step is initializing the neural network using statistical clustering, and the second is to reduce the concealing units of neural network according to the training situation. Using this, the generalization of neural network can be improved and the Over-fitting phenomenon can be reduced. With experimental contract to LSC algorithm, SCRBF is effective.