A machine learning problem assessment system that identifies potential machine learning problems in a machine learning system in which learning code evaluates data to correlate estimated learned data with data patterns. An accessing component accesses the learning code and/or the data that the learning code evaluates. A problem identifies component estimates, based on the accessed code and/or data, that there is a potential problem with machine learning system. A rectification component at least partially automatically rectifies the identified potential problem with the machine learning system by performing a computerized action on the machine learning system. The identified potential problem may affect quality (e.g., appropriateness of conclusions) and/or performance (e.g., speed) of the learning of the machine learning system.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A machine learning problem assessment system that identified potential machine learning problems in a machine learning system in which learning code evaluates data to correlate estimated learned data with data patterns, the machine learning problem estimation system comprising: an accessing component that accesses at least one of 1) the learning code, and 2) the data that the learning code evaluates; a problem identification component that identifies, based on the accessed code and/or data, that there is a potential problem with machine learning system; and a rectification component that at least partially automatically rectifies the potential problem with the machine learning system by performing a computerized action on the machine learning system. 2. The machine learning problem assessment system in accordance with claim 1, the problem identification component further identifying based on evaluation of at least one of a plurality of processing stages of the learning code. 3. The machine learning problem assessment system in accordance with claim 1, the rectification component automatically rectifying the identified potential problem with the machine learning system. 4. The machine learning problem assessment system in accordance with claim 1, the rectification component causing at least one solution to the identified potential problem to be presented to the user along with an approval control that the user may actuate to trigger the rectification component to automatically rectify the identified potential problem with the machine learning system. 5. The machine learning problem assessment system in accordance with claim 4, the rectification component also causing a description of the identified potential problem to be displayed to the user. 6. The machine learning problem assessment system in accordance with claim 1, the identified potential problem being underfitting of the data to the learning code. 7. The machine learning problem assessment system in accordance with claim 1, the identified potential problem being overfitting of the data to the learning code. 8. The machine learning problem assessment system in accordance with claim 1, the identified potential problem being improper scoring of the learning code. 9. The machine learning problem assessment system in accordance with claim 1, the computerized action comprising switching the learning code for other learning code. 10. The machine learning problem assessment system in accordance with claim 1, the computerized action comprising adjusting the learning code. 11. The machine learning problem assessment system in accordance with claim 10, the adjusting of the learning code comprising regularization of the learning code. 12. The machine learning problem assessment system in accordance with claim 1, the computerized action comprising augmenting the data that is used by the learning code. 13. The machine learning problem assessment system in accordance with claim 1, the computerized action comprising preparing the data that is used by the learning code. 14. The machine learning problem assessment system in accordance with claim 1, the estimated problem being failure to properly split the data between use in training and scoring. 15. The machine learning problem assessment system in accordance with claim 14, the computerized action comprising creating a different split of the data between use in training and scoring. 16. The machine learning problem assessment system in accordance with claim 14, the computerized action comprising creating a non-overlapping split of the data between use in training and scoring. 17. The machine learning problem assessment system in accordance with claim 1, the identified potential problem being insufficiently stratification in the data. 18. The machine learning problem assessment system in accordance with claim 17, the computerized action being performing further stratification of the data. 19. A computer program product comprising one or more computer-readable storage media having thereon computer-executable instructions that are structure such that, when executed by one or more processors of the computing system, configure the computing system to instantiate and/or operate a plurality of executable components in a machine learning problem assessment system that identifies potential machine learning problems in a machine learning system in which learning code evaluates data to correlate estimated learned data with data patterns, the plurality of executable components comprising: an accessing component that accesses at least one of 1) the learning code, and 2) the data that the learning code evaluates; a problem identification component that identifies, based on the accessed code and/or data, that there is a potential problem with machine learning system; and a rectification component that at least partially automatically rectifies the identified potential problem with the machine learning system by performing a computerized action on the machine learning system. 20. A method for a machine learning problem assessment system to identify potential machine learning problems in a machine learning system in which learning code evaluates data to correlate estimated learned data with data patterns, the method comprising: an act of an accessing component accessing at least one of 1) the learning code, and 2) the data that the learning code evaluates; an act of a problem identification component identifying, based on the accessed code and/or data, that there is a potential problem with machine learning system; and an act of a rectification component at least partially automatically rectifying the identified potential problem with the machine learning system by performing a computerized action on the machine learning system. 21. The method in accordance with claim 20, the identified potential problem affecting quality of learning of the machine learning system. 22. The method in accordance with claim 20, the identified potential problem affecting performance of the machine learning system.