Automated machine learning model generation using correlation between attributes

A computer system comprising:

• a processor set;
• a set of one or more computer-readable storage media;
• and
• program instructions, collectively stored in the set of one or more storage media, for causing the processor set to perform computer operations comprising:
• accessing table data within a database, the table data comprising columns corresponding to candidate attributes, respectively, and a target column corresponding to a target attribute;
• determining, by executing an entropy function, entropy values of the candidate attributes based on randomness of values in the columns corresponding to the candidate attributes, respectively;
• identifying a subset of candidate attributes among the candidate attributes which have entropy values between a predefined range of entropy values;
• determining a correlation between the subset of attributes by executing a correlation function on values in columns corresponding to the subset of candidate attributes;
• identifying at least one machine learning (ML) model to be generated based on the correlation between the subset of candidate attributes;
• and
• training the at least one ML model to determine the target attribute based on execution of the at least one ML model on training data to generate a trained at least one ML model.

A computer program product comprising:

• a set of one or more computer-readable storage media;
• and
• program instructions, collectively stored in the set of one or more computer-readable storage media, for causing a processor set to perform computer operations comprising:
• accessing table data within a database, the table data comprising columns corresponding to candidate attributes, respectively, and a target column corresponding to a target attribute;
• determining, by executing an entropy function, entropy values of the candidate attributes based on randomness of values in the columns corresponding to the candidate attributes, respectively;
• identifying a subset of candidate attributes among the candidate attributes which have entropy values between a predefined range of entropy values;
• determining a correlation between the subset of attributes by executing a correlation function on values in columns corresponding to the subset of candidate attributes;
• identifying at least one machine learning (ML) model to be generated based on the correlation between the subset of candidate attributes;
• and
• training the at least one ML model to determine the target attribute based on execution of the at least one ML model on training data to generate a trained at least one ML model.