Machine learning feature recommendation

A system, comprising:

• processing circuitry;
• and
• memory, accessible by the processing circuitry, the memory storing instructions that, when executed by the processing circuitry, cause the processing circuitry to perform operations comprising:
• receiving, via a user interface, a command to initiate creation of a machine learning model;
• receiving, via the user interface, an indication of a target field, within one or more database tables storing a plurality of sets of machine learning training data, for the machine learning model to predict;
• automatically identifying, within the one or more database tables, one or more eligible machine learning features to predict the target field;
• automatically evaluating a level of impact of each of the eligible machine learning features on a prediction accuracy of the machine learning model;
• generating, via the user interface, a set of recommended machine learning features, from the one or more eligible machine learning features, wherein the set of recommended machine learning features are ranked based on the respective levels of impact on the prediction accuracy of the machine learning model;
• and
• automatically selecting one or more of the eligible machine learning features with which to build the machine learning model.

A non-transitory computer-readable storage medium, comprising processor-executable routines that, when executed by a processor, cause the processor to perform operations comprising:

• receiving, via a user interface, a command to initiate creation of a machine learning model;
• receiving, via the user interface, an indication of a target field, within one or more database tables storing a plurality of sets of machine learning training data, for the machine learning model to predict;
• automatically identifying, within the one or more database tables, one or more eligible machine learning features to predict the target field;
• automatically evaluating a level of impact of each of the eligible machine learning features on a prediction accuracy of the machine learning model;
• generating, via the user interface, a set of recommended machine learning features, from the one or more eligible machine learning features, wherein the set of recommended machine learning features are ranked based on the respective levels of impact on the prediction accuracy of the machine learning model;
• and
• receiving, via the user interface, an input identifying one or more selected machine learning features.