A hybrid anomaly detection method for high dimensional data
Anomaly detection of high-dimensional data is a challenge because the sparsity of the data distribution caused by high dimensionality hardly provides rich information distinguishing anomalous instances from normal instances.To address Tote Bag this, this article proposes an anomaly detection method combining an autoencoder and a sparse weighted lea