Predictive compliance testing for early screening

A method of predicting an outcome of a compliance testing of a test target, the method comprising:

• identifying determinate factors and indeterminate factors from a set of factors associated with a current testing stage of the compliance testing, wherein a first factor value for each of the determinate factors is available and a second factor value for each of the indeterminate factors is unavailable for the current testing stage;
• generating a test vector for each of the indeterminate factors, wherein the test vector for each of the indeterminate factors is generated based on a set of test attributes associated with a corresponding indeterminate factor;
• determining a set of matching test vectors for each of the indeterminate factors based on the test vector, wherein the set of matching test vectors are determined using data extracted from at least one profile model;
• determining a cumulative factor value for each of the indeterminate factors based on the set of matching test vectors, wherein each matching test vector within the set of matching test vectors comprises a test value, and the test value is determined based on a weighted average of values of the test attributes;
• determining, for each of the determinate factors, a first outcome corresponding to the at least one profile model;
• generating, for each of the indeterminate factors using a corresponding machine learning algorithm, a second outcome based on the cumulative factor value and the set of matching test vectors extracted from the at least one profile model, wherein the at least one profile model corresponds to at least one target parameter;
• and
• generating a compliance prediction at the current testing stage of the test target for the at least one target parameter based on the first outcome and the second outcome.

A compliance test system for generating a compliance prediction for a test target, the compliance test system comprising:

• a vector generating server comprising a processor and memory with instructions configured to:
• identify determinate factors and indeterminate factors from a set of factors associated with a current testing stage of the compliance test system, wherein a first factor value for each of the determinate factors is available and a second factor value for each of the indeterminate factors is unavailable for the current testing stage;
• and
• generate a test vector for each of the indeterminate factors, wherein the test vector for each of the indeterminate factors is generated based on a set of parameters associated with a corresponding indeterminate factor;
• a vector matching server comprising a processor and memory with instructions configured to:
• determine a set of matching test vectors for each of the indeterminate factors based on the test vector, wherein the set of matching test vectors are determined using data extracted from at least one profile model;
• a vector processing server comprising a processor and memory with instructions configured to:
• determine a cumulative factor value for each of the indeterminate factors based on the set of matching test vectors, wherein each matching test vector within the set of matching test vectors comprises a test value, the test value is determined based on a weighted average of values of the parameters;
• determine, for each of the determinate factors, a first outcome corresponding to the at least one profile model;
• and
• generate, for each of the indeterminate factors using a corresponding machine learning algorithm, a second outcome based on the cumulative factor value and the set of matching test vectors extracted from the at least one profile model, wherein the at least one profile model corresponds to at least one target parameter;
• and
• a prediction engine comprising a processor and memory with instructions configured to:
• generate the compliance prediction at the current testing stage of the test target for the at least one target parameter based on the first outcome and the second outcome.