A method of identifying an element. The method comprises setting a training set comprising a plurality of data units, selecting a function group of building block functions adapted for processing said plurality of data units, combining members of said function group to create a stream of a plurality of combination functions each complied from at least two members of said function group, applying each member of said stream on each of said plurality of data units to create a set of results, analyzing said set of results to identify a correlation between at least one member of said stream and a target variable for an analysis of said plurality of data units, and outputting said at least one member or an indication thereof.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of identifying an element, comprising: setting a training set comprising a plurality of data units; selecting a function group of building block functions adapted for processing said plurality of data units; combining members of said function group to create a stream of a plurality of combination functions each complied from at least two members of said function group; applying each member of said stream on each of said plurality of data units to create a set of results; analyzing said set of results to identify a correlation between at least one member of said stream and a target variable for an analysis of said plurality of data units; and outputting said at least one member or an indication thereof. 2. The method of claim 1, wherein said set of results comprises a plurality of feature vectors each generated by applying one of said members of said function group on each of said plurality of data units. 3. The method of claim 2, wherein said target variable is a classification at a desired ratio; said analyzing comprises identifying which of said plurality of feature vectors having features classified at said desired ratio. 4. The method of claim 1, wherein said combining comprises using an output parameter of a first member of said function group as in input parameter of a second member of said function group. 5. The method of claim 1, wherein said combining comprises mapping a statistical usage of members of said function group in a plurality of code samples and selecting members of said function group for creating said plurality of combination functions according to said mapping. 6. The method of claim 1, wherein said combining comprises mapping a statistical usage of members of said function group in a plurality of code samples and defining an order for applying said members of said function group according to said mapping. 7. The method of claim 1, wherein said selecting comprises: analyzing said plurality of data units to identify automatically at least one common data type; and selecting said function group of building block functions according to said at least one common data type from a dataset of a plurality of building block functions. 8. The method of claim 7, wherein said selecting said function group of building block functions is performed using a hierarchal data type model. 9. The method of claim 7, wherein said selecting said function group of building block functions is performed according to available data unit type conversion functions. 10. The method of claim 7, wherein said plurality of building block functions are clustered to a plurality of function clusters each associated with at least one data unit type; wherein said selecting comprises matching between said common data type and a respective said at least one data unit type of at least one of said plurality of function clusters; and selecting said at least one function cluster as said function group. 11. The method of claim 1, wherein each of said plurality of combination functions is generated by compiling at least two members of said function group as nodes of a tree representing a respective said combination function. 12. The method of claim 11, wherein said tree is an abstract syntax tree (AST). 13. The method of claim 1, wherein each of said plurality of combination functions is generated to comply with a set of constraint rules. 14. The method of claim 1, wherein said at least one member is a function for classifying data. 15. The method of claim 1, wherein said at least one member is a predictive function for predicting an outcome or an event. 16. A system of identifying an element, comprising: an interface which accesses a training set comprising a plurality of data units; a processor; an interface which accesses a function dataset to select a function group of building block functions adapted for processing said plurality of data units; a selection module which uses said processor to combine members of said function group to create a stream of a plurality of combination functions each complied from at least two members of said function group, to apply each member of said stream on each of said plurality of data units to create a set of results, to analyze said set of results to identify a correlation between at least one member of said stream and a target variable for an analysis of said plurality of data units, and to output said at least one member or an indication thereof. 17. A computer program product for identifying an element, comprising: a computer readable storage medium; first program instructions to set a training set comprising a plurality of data units; second program instructions to select a function group of building block functions adapted for processing said plurality of data units; third program instructions to combine members of said function group to create a stream of a plurality of combination functions each complied from at least two members of said function group; fourth program instructions to apply each member of said stream on each of said plurality of data units to create a set of results; fifth program instructions to analyze said set of results to identify a correlation between at least one member of said stream and a target variable for an analysis said plurality of data units; and sixth program instructions to output said at least one member or an indication thereof; wherein said first, second, third, fourth, fifth, and sixth program instructions are stored on said computer readable storage medium. 18. A method of identifying an element, comprising: setting a training set comprising a plurality of data units; selecting a function group of functions adapted for processing said plurality of data units for generating a stream of functions; applying each member of said stream of functions on each of said plurality of data units to create a set of results; analyzing said set of results to identify a correlation between at least one member of said stream of functions and a target variable for an analysis of said plurality of data units; and outputting said at least one member or an indication thereof.