SYSTEMS AND METHODS FOR ACTIVE ALGORITHM TRAINING IN A ZERO-TRUST ENVIRONMENT

Systems and methods for providing algorithm performance feedback to an algorithm developer is provided In some embodiments, an algorithm and a data set are receiving within a secure computing node. The data set is processed using the algorithm to generate an algorithm output. A raw performance model is generated by regression modeling the algorithm output. The raw performance model is then smoothed to generate a final performance model, which is then encrypted and routed to an algorithm developer for further analysis. The performance model models at least one of the algorithm's accuracy, F1 score accuracy, precision, recall, dice score, ROC (receiver operator characteristic) curve/area, log loss, Jaccard index, error, R2 or by some combination thereof. The regression modeling includes linear least squares, logistic regression, deep learning or some combination thereof.