Systems and Methods for Computer Modeling Using Incomplete Data

Abstract

Systems and methods for dynamic computer modeling using incomplete data are provided. The system can yield a total score indicative of an accuracy and reliability of a model for a given application based on incomplete data. The system can receive one or more sets of datasets, classify each dataset among the set of datasets based on a classification component, and determine a normalized score for each dataset based on a value or values of each dataset. If a classification component does not comprise more than one dataset, then the system determines a classification component score for each dataset as the normalized score. If a classification component comprises more than one dataset, the system assigns a weighted data value to each dataset of the classification component. A classification component score is determined for each weighed dataset by applying the weighted data value to the normalized score for each weighed dataset. A final component score for each dataset is determined by applying a weighted classification component value to the classification component score for each dataset.

What is claimed is: 
     
         1 . A system for dynamic computer modeling using incomplete data, comprising:
 a processor in communication with a database; and   machine-readable system code executed by the processor, the code causing the processor to:
 receive a plurality of datasets from the database, at least one of the plurality of datasets including incomplete data; 
 process each of the plurality of datasets to classify each dataset based on a classification component; 
 determine a normalized score for each dataset based on at least one value in each dataset; 
 determine a classification component score for each dataset; 
 determine a total score for the plurality of datasets by aggregating the classification component scores, the total score indicating accuracy and reliability of a model corresponding to the plurality of datasets; and 
 transmitting the total score to a recipient. 
   
     
     
         2 . The system of  claim 1 , wherein the code causes the processor to determine whether a classification component comprises more than one dataset. 
     
     
         3 . The system of  claim 2 , wherein the code causes the processor to determine the classification component score for each of the datasets as the normalized score for each dataset if the classification component does not comprise more than one dataset. 
     
     
         4 . The system of  claim 2 , wherein the code causes the processor to assign a weighted data value to each dataset of the classification component if the classification component comprises more than one dataset. 
     
     
         5 . The system of  claim 4 , wherein the code causes the processor to determine the classification component score for each weighted dataset by applying the weighted data value to the normalized score for each weighted dataset. 
     
     
         6 . A method for dynamic computer modeling using incomplete data, comprising the steps of:
 receiving at a processor a plurality of datasets from the database, at least one of the plurality of datasets including incomplete data;   process each of the plurality of datasets by the processor to classify each dataset based on a classification component;   determine by the processor a normalized score for each dataset based on at least one value in each dataset;   determine by the processor a classification component score for each dataset;   determine by the processor a total score for the plurality of datasets by aggregating the classification component scores, the total score indicating accuracy and reliability of a model corresponding to the plurality of datasets; and   transmitting the total score to a recipient.   
     
     
         7 . The method of  claim 6 , further comprising determining by the processor whether a classification component comprises more than one dataset. 
     
     
         8 . The method of  claim 7 , further comprising determining by the processor the classification component score for each of the datasets as the normalized score for each dataset if the classification component does not comprise more than one dataset. 
     
     
         9 . The method of  claim 7 , further comprising assigning by the processor a weighted data value to each dataset of the classification component if the classification component comprises more than one dataset. 
     
     
         10 . The method of  claim 9 , further comprising determining by the processor the classification component score for each weighted dataset by applying the weighted data value to the normalized score for each weighted dataset.