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. A method for automatically selecting from a plurality of analytic algorithms a best performing analytic algorithm to apply to a dataset, comprising: training, by a processor coupled to a memory, a plurality of analytic algorithms on a plurality of subsets of the dataset; estimating, by the processor, a corresponding prediction accuracy trend across the subsets for each of the plurality of analytic algorithms to produce a plurality of accuracy trends; selecting, by the processor, 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, by the processor, the best performing analytic algorithm. 2. The method of claim 1, wherein the processor executes 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. 3. The method of claim 1, wherein each corresponding prediction accuracy trend is a normalized line calculated across the subsets of the plurality of analytic algorithms. 4. The method of claim 1, 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. 5. The method of claim 1, wherein the training of the plurality of analytic algorithms is responsive to an input comprising the dataset, the plurality of analytic algorithms, and a validation set. 6. The method of claim 1, wherein the dataset is prepared data derived from raw data through ingestion, cleansing, and transformation operations. 7. The method of claim 1, wherein the training of the plurality of analytic algorithms, comprises: allocating each of the plurality of analytic algorithms to the dataset. 8. The method of claim 1, 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.