A system, method, and computer program product for automatically selecting from a plurality of analytic algorithms a best performing analytic algorithm to apply to a dataset is provided. The automatically selecting from the plurality of analytic algorithms the best performing analytic algorithm to apply to the dataset enables a training a plurality of analytic algorithms on a plurality of subsets of the dataset. Then, a corresponding prediction accuracy trend is estimated across the subsets for each of the plurality of analytic algorithms to produce a plurality of accuracy trends. Next, the best performing analytic algorithm is selected and outputted from the plurality of analytic algorithms based on the corresponding prediction accuracy trend with a highest value from the plurality of accuracy trends.
Please help me write a proper abstract based on the patent claims. CLAIM: 1.-8. (canceled) 9. A system for automatically selecting from a plurality of analytic algorithms a best performing analytic algorithm to apply to a dataset, comprising: a memory having computer readable instructions; and a processor for executing the computer readable instructions, the computer readable instructions including operations comprising: training a plurality of analytic algorithms on a plurality of subsets of the dataset; estimating a corresponding prediction accuracy trend across the subsets for each of the plurality of analytic algorithms to produce a plurality of accuracy trends; selecting the best performing analytic algorithm from the plurality of analytic algorithms based on the corresponding prediction accuracy trend with a highest value from the plurality of accuracy trends; and outputting the best performing analytic algorithm. 10. The system of claim 9, wherein the computer readable instructions include executing a data allocation using estimates of upper bounds on accuracies to perform the training of the plurality of analytic algorithms and the estimating of the plurality of accuracy trends. 11. The system of claim 9, wherein each corresponding prediction accuracy trend is a normalized line calculated across the subsets of each of the plurality of analytic algorithms. 12. The system of claim 9, wherein the selecting of the best performing analytic algorithm, comprises: selecting from the plurality of analytic algorithms as the best performing analytic algorithm an algorithm that has a most optimistic upper bound. 13. The system of claim 9, wherein training of the plurality of analytic algorithms is responsive to an input comprising the dataset, the plurality of analytic algorithms, and a validation set. 14. The system of claim 9, wherein the dataset is prepared data derived from raw data through ingestion, cleansing, and transformation operations. 15. The system of claim 9, wherein the training of the plurality of analytic, comprises: allocating each of the plurality of analytic algorithms to the dataset. 16. The system of claim 9, wherein the outputting of the best performing analytic algorithm, comprises: displaying a smart graphic user interface presenting a visualization of the best performing analytic algorithm. 17. A computer program product for automatically selecting from a plurality of analytic algorithms a best performing analytic algorithm to apply to a dataset, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform operations comprising: training a plurality of analytic algorithms on a plurality of subsets of the dataset; estimating a corresponding prediction accuracy trend across the subsets for each of the plurality of analytic algorithms to produce a plurality of accuracy trends; selecting the best performing analytic algorithm from the plurality of analytic algorithms based on the corresponding prediction accuracy trend with a highest value from the plurality of accuracy trends; and outputting the best performing analytic algorithm. 18. The computer program product of claim 17, wherein the program instructions include a data allocation using estimates of upper bounds on accuracies to perform the training of the plurality of analytic algorithms and the estimating of the plurality of accuracy trends. 19. The computer program product of claim 17, wherein each corresponding prediction accuracy trend is a normalized line calculated across the subsets of the plurality of analytic algorithms. 20. The computer program product of claim 17, wherein the selecting of the best performing analytic algorithm, comprises: selecting from the plurality of analytic algorithms as the best performing analytic algorithm an algorithm that has a most optimistic upper bound. 21. The computer program product of claim 17, wherein training of the plurality of analytic algorithms is responsive to an input comprising the dataset, the plurality of analytic algorithms, and a validation set. 22. The computer program product of claim 17, wherein the dataset is prepared data derived from raw data through ingestion, cleansing, and transformation operations. 23. The computer program product of claim 17, wherein the training of the plurality of analytic, comprises: allocating each of the plurality of analytic algorithms to the dataset. 24. The computer program product of claim 17, wherein the outputting of the best performing analytic algorithm, comprises: displaying a smart graphic user interface presenting a visualization of the best performing analytic algorithm.