An Optimized Pruning-based Outlier Detecting algorithm is proposed based on the density-based outlier detecting algorithm (LOF algorithm). The calculation accuracy and the time complexity of LOF algorithm are not ideal, so two steps are taken to reduce the amount of calculation and improve the calculation accuracy for LOF algorithm. Firstly, using cluster pruning technique to preprocess data set, at the same time filtering the non-outliers based on the differences of cluster models to avoid the error pruning of outliers located at the edge of clusters, different cluster models are output by in...
