Patent ID: 9324041
Filing Date: 2016-04-26
CPC Classification: G06N

Claim Text:
1. A computer-implemented method of identifying at least one classifying or predictive function which outputs at least one data classifying or predicting feature when applied on a set of data units of a certain type, comprising: accessing, by said processor via an interface, a training set stored as a computer readable data sample of various types and forms in a data sample database, said training set comprising a plurality of data units representing a member selected from the group consisting of: records, events, measurements, estimation, and evaluation; selecting, by said processor, a function group of building block functions which are adapted for processing said plurality of data units, said building block functions stored in a function database accessible by said processor via said interface; combining, by said processor, building block function members of said function group to create a a plurality of composed functions each compiled from at least two building block function members of said function group; generating a stream of functions from said composed functions, wherein said stream includes an infinite or a finite number of composed function members; applying, by said processor, each composed function member of said stream on each of said plurality of data units to create a set of results; analyzing, by said processor, said set of results to identify at least one composed function member of said stream according to a correlation between an outcome of said respective composed function member and a target variable for an analysis of said plurality of data units; and outputting, by said processor, said at least one composed function member or an indication thereof; wherein said at least one composed function member or indication thereof includes a classifying or predictive function which outputs at least one data classifying or predicting features when applied on a set of data units of a certain type.