Based on Rough Sets and L1 Regularization of the Fault Diagnosis of Linear Regression Model

The purpose of this article is to network fault diagnosis, a higher knowledge more than soft, using least squares estimation precision, low efficiency, thus put forward the new type of rough sets and L1 regularization method network fault diagnosis model. Thus obtained in the network fault diagnosis for large amounts of data regression fitting its computational efficiency, diagnostic accuracy, stability has improved significantly.