6. The method of claim 1 , wherein generating the predictive analytic model and runtime query, using the user-defined predictive analytics query, further comprises: receiving the user-defined predictive analytics query as input; identifying the predictive analytics by-example vocabularies; extracting the subject-specific by-example vocabularies from the user-defined predictive analytics query received as input; validating correct sequencing of one or more by-example keywords using rules of the set of syntactic grammar; and analyzing the predictive analytics by-example vocabularies in the user-defined predictive analytics query received, together with a data type of the subject-specific by-example vocabularies, to determine semantics of the user-defined predictive analytics query received, including an associated predictive analytics model and predictive analytics command to generate, wherein a generator uses decisions of a parser to perform at least one of constructing an instance of the predictive analytics model along with corresponding commands and selecting an existing model to reuse.
1. A computer-implemented method for predictive analytic queries, the computer-implemented method comprising: creating a set of predictive analytics by-example vocabularies; creating a set of subject-specific by-example vocabularies, each comprising one or more nouns associated with a respective subject area, wherein the one or more subject-specific by-example vocabularies are based on a capability of one or more data sources; generating a palette of vocabularies for constructing predictive queries, wherein the palette of vocabularies is based on the set of predictive analytics by-example vocabularies and the set of subject-specific by-example vocabularies; constructing a user-defined predictive analytics query comprising the palette of vocabularies using a set of syntactic grammar that defines a correct syntax of the user-defined predictive analytic query; wherein the set of syntactic grammar defines semantics of each syntactically correct predictive analytics query using the palette of vocabularies, such that the user-defined predictive analytics query is expressed with semantic precision using a constrained Natural Language Processing (cNLP) approach; generating, by a computer processor, a predictive analytic model and runtime query, using the user-defined predictive analytics query; executing the runtime query using the predictive analytic model to create a result; and returning the result to a user.