Algorithm Optimization of Anomaly Detection Based on Data Mining
In this paper, firstly two improved algorithm methods are introduced, namely INFLOF and COF, which are based on LOF, then the motivation of each algorithm, the definition of the algorithm and the specific steps of the algorithm are described respectively. Then through summarizing LOF, INFLOF and COF it can find out the intrinsic link between them: INFLOF can solve the problem of edge misjudgment caused by different density cluster's closing to each other in data set, while COF can solve the problem of outliers, but these kinds of two algorithms are from different steps to solve the outlier factor. Finally, the advantages of the these two algorithms are presented, thus the algorithm of this paper is introduced. Moreover, the definition of the algorithm, as well as the specific steps of the algorithm is respectively introduced, besides it also analyzed the time complexity of algorithm.