Systems and methods for preparing data for use by machine learning algorithms

In a system for preparing a plurality of historical data records for use in training a primary model machine learning algorithm, wherein each historical data record includes a plurality of fields containing data values designated as inputs for training the primary model machine learning algorithm to generate an output of interest, a computer-implemented method of preparing the designated inputs in the plurality of historical data records in order to increase the utility and accuracy of the trained primary model machine learning algorithm when the designated inputs in the historical data records include invalid data values, the method comprising:

• segregating a base dataset containing the historical data records into a faulty dataset having incomplete data records with invalid data values and a clean dataset having complete data records with no invalid data values;
• storing the faulty dataset and the clean dataset in a computer memory;
• producing from the stored clean dataset at least one of (i) plural computer-implemented secondary model machine learning algorithms trained to generate from values of the respective fields designated as inputs in plural complete data records a replacement value for a single invalid data value in a corresponding field designated as an input in an incomplete data record, and (ii) a computer-implemented tertiary model machine learning clustering algorithm trained to generate from plural complete data records comprising all values of fields designated as inputs replacement values for multiple invalid data values designated as inputs in an incomplete data record;
• and
• using a computer-implemented program to create augmented training data records by substituting the replacement data values for at least some of the respective invalid data values designated as inputs in the stored faulty dataset, whereby said augmented training data records can be used with complete data records in the clean dataset to train the primary model machine learning algorithm to improve the accuracy thereof when generating an output of interest from a new data record.