Local outlier factor algorithm based on correction of bidirectional neighbor

A local outlier factor algorithm based on bidirectional neighbor correction was proposed to solve the problems of existing outlier detection algorithms such as difficulty in parameter selection,poor efficiency and low accuracy.The bidirectional neighbor searching algorithm was used to reduce the neighbor search time.Then the bidirectional neighbor pruning algorithm was used to reduce the number of parameters and unnecessary calculations.And the correction factor based on bidirectional neighbors was used to improve the calculation accuracy.Experimental results show that the proposed algorithm has better performance in parameter selection and time efficiency than other outlier detection methods.The correction factor improves the accuracy of the algorithm,in the synthetic data set and UCI data set.