Machine learning semantic model
作者： Ioan Bogdan Crivat , C. James MacLennan
DOI:
关键词: Predictive Model Markup Language 、 Data mining 、 Subject (documents) 、 Machine learning 、 Semantic data model 、 Event (probability theory) 、 Test set 、 Computer science 、 Artificial intelligence 、 Constraint (information theory) 、 Data source 、 Set (abstract data type)
摘要: The subject technology discloses configurations for creating reusable predictive models applying to one or more data sources. specifies a business problem determine probability of an event occurring. may include constraint. A source is selected model associated with algorithm in which the includes queries and parameters. set transformations are then determined based on parameters at least subset from be processed by algorithm. identifies patterns source. trained provided including patterns, transformations, solving specified problem.
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