A Training Method of Natural Language Corpus for the Decision Making Model of Machine Learning implemented by a computer device, the computer device stores a plurality of natural texts, each of natural text is marked with a target decision result of a plurality of decision results and includes a plurality of reasoning data related to at least one object to be described by the natural text, and includes: For each reasoning data corresponding to each natural text, a segmentation of word algorithm and a document-to-vector algorithm are used to obtain a corresponding reasoning vector group; For each natural text, the reasoning vector groups corresponding to the natural text are combined into an effective vector according to the sequential connection; Obtaining a decision model by using a supervised classification algorithm according to the effective vector corresponding to each natural text and its corresponding target decision result. |