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 this. this article proposes an anomaly detection method combining an autoencoder and a sparse weighted least squares-support vector machine. First. https://herbsdailyes.shop/product-category/fabric-refreshers/