14. A system comprising: a data store including a set of verified documents and a set of unverified documents, the set of verified documents divided into a training set of documents and a test set of documents, the training set of documents divided into an integer number of verified document sets (INVDS), and the set of unverified documents divided into an integer number of unverified document sets (UNVDS); a server including a processor and memory operatively coupled to the data store, the memory storing instructions that, in response to receiving a request for access to a service, cause the processor to: automatically identify a subset of documents from the UNVDS in response to inputting the set of unverified documents into an initially trained classifier (ITC); automatically generate a final set of training documents based on the subset of documents and the INVDS; clustering at least one subset of documents from the INVDS and one subset of documents from the UNVDS using a flat clustering or hierarchical clustering technique; and train the ITC using the final set of training documents.
14. A system comprising: a data store including a set of verified documents and a set of unverified documents, the set of verified documents divided into a training set of documents and a test set of documents, the training set of documents divided into an integer number of verified document sets (INVDS), and the set of unverified documents divided into an integer number of unverified document sets (UNVDS); a server including a processor and memory operatively coupled to the data store, the memory storing instructions that, in response to receiving a request for access to a service, cause the processor to: automatically identify a subset of documents from the UNVDS in response to inputting the set of unverified documents into an initially trained classifier (ITC); automatically generate a final set of training documents based on the subset of documents and the INVDS; clustering at least one subset of documents from the INVDS and one subset of documents from the UNVDS using a flat clustering or hierarchical clustering technique; and train the ITC using the final set of training documents. 15. The system of claim 14 , wherein the memory stores instructions that, in response to receiving the request, cause the processor to: execute a first loop code segment comprising a first loop construct, wherein the first loop code segment is executed at run time at least n times, wherein n is a value at run time of a first variable in a first loop termination condition; execute a second loop code segment comprising a second loop construct, wherein the second loop code segment is executed at least p×n times, wherein p is a value at run time of a second variable in a second loop termination condition; and execute a third loop code segment comprising a third loop construct, wherein the third loop code segment is executed p×n×q times, wherein q is a value at run time of a third variable in a third loop termination condition.