Learning-based drift detection tool

A computer system for generating a drift detector, the system comprising:

• a memory;
• and
• a processor system communicatively coupled to the memory;
• wherein the processor system configured to perform a method comprising:
• generating drift cases based at least in part on known drift set data of a computer system;
• injecting the drift cases into the computer system to generate a first data set;
• applying cleaning rules to the first data set to reduce a size of the first data set and generate a cleaned data set;
• extracting one or more features of the cleaned data set;
• normalizing the one or more features of the cleaned data set;
• and
• training a machine learning system using the extracted and normalized one or more features of the cleaned data;
• wherein an output of the machine learning system comprises the drift detector.

A computer program product for generating a drift detector, the computer program product comprising:

• a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions readable by a processor system to cause the processor system to perform a method comprising:
• generating drift cases based at least in part on known drift set data of a computer system;
• injecting the drift cases into the computer system to generate a first data set;
• applying cleaning rules to the first data set to reduce a size of the first data set and generate a cleaned data set;
• extracting one or more features of the cleaned data set;
• normalizing the one or more features of the cleaned data set;
• and
• training a machine learning system using the extracted and normalized one or more features of the cleaned data;
• wherein an output of the machine learning system comprises the drift detector.