Memoizing machine-learning pre-processing and feature engineering

A method creates a table of keys and values. Each key is an element of an input array which is an input of a machine-learning pre-processing pipeline, and each value is an output of the pipeline. The method measures (1) a hit rate H to the memo table, (2) an average time Ttable to look up the table, (3) an average time Tpipeline to execute the pipeline, and (4) a threshold Telements on a number of elements of the input array. The method looks up the value in the table by using an element of the input array as a key when Tpipeline×H>Ttable and the number of elements in the input array is less than Telements. The method calls the pipeline in place of the lookup for all of the remaining elements in the input array when the value is not in the table.