CPC G06N 5/04 (2013.01) [G06N 20/00 (2019.01)] | 16 Claims |
1. A computer-implemented method comprising:
receiving a dataset for processing by a machine learning model (MLM);
receiving a scoring payload comprising a set of information related to operation of the MLM using the dataset;
determining a set of features of the machine learning model by analyzing the scoring payload;
determining prediction results that are predicted to be produced by the MLM for the scoring payload by analyzing fields within the scoring payload; and
structuring the scoring payload in accordance with the set of features such that the structured scoring payload is ready for analysis for a monitor of the machine learning model, wherein the structuring utilizes a technique selected from the group consisting of a classification technique, a correlation technique, and a direct value identification technique;
wherein:
the set of features is determined by a controller that includes a second MLM that utilizes a multioutput multiclass classification technique;
the set of features comprises:
a learning framework of the machine learning model;
a service provider of the machine learning model;
a problem type for the scoring payload; and
whether a result of the scoring payload is an encoded target or a decoded target;
the method further comprising:
sending the structured scoring payload from the controller to the monitor for determining a health of the MLM.
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