Failure feedback system for enhancing machine learning accuracy by synthetic data generation

Abstract

An exemplary system, method, and computer-accessible medium can include, for example, (a) receiving a dataset(s), (b) determining if a misclassification(s) is generated during a training of a model(s) on the dataset(s), (c) generating a synthetic dataset(s) based on the misclassification(s), and (d) determining if the misclassification(s) is generated during the training of the model(s) on the synthetic dataset(s). The dataset(s) can include a plurality of data types. The misclassification(s) can be determined by determining if one of the data types is misclassified. The dataset(s) can include an identification of each of the data types in the dataset(s).

1 - 40 . (canceled) 
     
     
         41 . A method performed by a computer hardware arrangement, the method comprising:
 training at least one model on at least one dataset including a plurality of data types;   determining at least one misclassification of one of the plurality of data types;   assigning a classification score to each of the plurality of data types;   receiving at least one synthetic dataset;   training the at least one model on the synthetic dataset; and   determining if the at least one misclassification is generated during the training of the at least one model on the at least one synthetic dataset based on the assigned classification score being below a particular threshold.