Generate alerts while monitoring a machine learning model in real time

A system to generate alerts while monitoring a machine learning model in real time, the system comprising:

• a memory;
• a processor coupled to the memory, wherein the processor is configured to execute programmed instructions stored in the memory for:
• receiving, in response to a first input parameter, a first output parameter generated by a first function of a learning model corresponding to a machine learning model;
• receiving, in response to a second input parameter, a second output parameter generated by a second functionality of a real-time model corresponding to the machine learning model, wherein the first functionality and the second functionality are configured to perform a same function;
• comparing the first output parameter with the second output parameter to determine an output variation score, wherein the comparison is based on a data type corresponding to the first output parameter and the second output parameter;
• comparing the first input parameter with the second input parameter to determine an input variation score, wherein the comparison is based on a data type corresponding to the first input parameter and the second input parameter;
• generating a tuning alert to tune the machine learning model, when the output variation score is above a first threshold value;
• and
• generating a model rebuilding alert to rebuild the machine learning model, when the input variation score is above a second threshold value.

A non-transitory computer readable medium embodying a program executable in a computing device to generate alerts while monitoring a machine learning model in real time, the computer program product comprising:

• a program code for receiving, in response to a first input parameter, a first output parameter generated by a first function of a learning model corresponding to a machine learning model;
• a program code for receiving, in response to a second input parameter, a second output parameter generated by a second functionality of a real-time model corresponding to the machine learning model, wherein the first functionality and the second functionality are configured to perform a same function;
• a program code for comparing, the first output parameter with the second output parameter to determine an output variation score, wherein the comparison is based on a data type corresponding to the first output parameter and the second output parameter;
• a program code for comparing, the first input parameter with the second input parameter to determine an input variation score, wherein the comparison is based on a data type corresponding to the first input parameter and the second input parameter;
• a program code for generating, a tuning alert to tune the machine learning model, when the output variation score is above a first threshold value;
• and
• a program code for generating, a model rebuilding alert to rebuild the machine learning model, when the input variation score is above a second threshold value.