Kernel methods on discrete domains have shown great promise for many challenging data types. for instance. biological sequence data and molecular structure data. Scalable kernel methods like Support Vector Machines may offer good predictive performances but do not intrinsically provide uncertainty estimates. https://allfixelectricales.shop/product-category/carpet-shampoo/