SAS Viya provides a comprehensive, collaborative visual interface for accomplishing all steps related to the analytical life cycle on a massively parallel processing infrastructure. Machine learning pipelines in Model Studio let you explore and compare multiple modeling approaches rapidly. You can quickly and easily find the optimal parameter settings for diverse machine learning algorithms – including decision trees, random forests, gradient boosting, neural networks, support vector machines and factorization machines – simply by selecting the option you want. Complex local search optimization routines work hard in the background to efficiently and effectively tune your models.
Contributors: Wendy Czika, Christian Medins, Radhikha Myneni, Ray Wright and Brett Wujek