Automated machine learning system

An apparatus comprising:

• one or more processors;
• and
• memory storing processor-executable instructions that, when executed by the one or more processors, cause the apparatus to:
• determine, based on a selection of a target metric, one or more data records associated with a prediction driver for the target metric;
• cause, based on the selection, a first machine learning model to output a first prediction score for the target metric, wherein the first prediction score is based on the one or more data records and the prediction driver;
• receive an adjustment to an amount of influence for the prediction driver, wherein the adjustment causes at least one value stored in each of the one or more data records to be replaced with a substitute value, and wherein the substitute value for each of the one or more data records is based on the at least one value stored in the corresponding data record and the adjustment to the amount of influence for the prediction driver;
• cause, based on the adjustment and the substitute value for each of the one or more data records, a second machine learning model to output a second prediction score for the target metric;
• and
• store, based on a further selection received, the first prediction score or the second prediction score, wherein the further selection is indicative of the first machine learning model or the second machine learning model.

One or more non-transitory computer-readable media storing processor-executable instructions that, when executed by one or more processors of at least one computing device, cause the at least one computing device to:

• determine, based on a selection of a target metric, one or more data records associated with a prediction driver for the target metric;
• cause, based on the selection, a first machine learning model to output a first prediction score for the target metric, wherein the first prediction score is based on the one or more data records and the prediction driver;
• receive an adjustment to an amount of influence for the prediction driver, wherein the adjustment causes at least one value stored in each of the one or more data records to be replaced with a substitute value, and wherein the substitute value for each of the one or more data records is based on the at least one value stored in the corresponding data record and the adjustment to the amount of influence for the prediction driver;
• cause, based on the adjustment and the substitute value for each of the one or more data records, a second machine learning model to output a second prediction score for the target metric;
• and
• store, based on a further selection received, the first prediction score or the second prediction score, wherein the further selection is indicative of the first machine learning model or the second machine learning model.