CPC G06F 18/217 (2023.01) [G06F 3/0484 (2013.01); G06N 3/08 (2013.01)] | 20 Claims |
1. A computer-implemented method for dynamic visualization of trained machine learning (ML) model performance on a graphical user interface (GUI), the method comprising:
receiving, from a user and by a user-adjustable artificial drift control of the GUI, data indicating a transformation to be applied to input samples;
applying the transformation to the input samples resulting in transformed input samples;
providing the transformed input samples to a trained ML model;
receiving data indicating the confidence and accuracy of the trained ML model with the transformed input samples as input, the confidence provided by the trained ML model and indicating an expected accuracy of a respective classifications by the trained ML model; and
dynamically displaying a concurrent plot of the accuracy and confidence to reflect the received data and as the received data are received.
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